SAP Community - Artificial Intelligence

SAP SuccessFactors Talent Intelligence Hub H1 2024 Release Insights

2024-04-28T23:21:16.825000+02:00

SAP SuccessFactors continues to set the bar high with its first half of 2024 release, particularly in the Talent Intelligence Hub and Succession & Development. This release packs exciting new features and essential updates that will transform how organisations manage and develop their workforce. Here’s an integrated overview of what’s new and noteworthy, with my insights and view

AI-Assisted Skills Architecture Creation: A Game Changer

The new AI-assisted skills architecture creation tool is a standout feature that addresses a significant challenge many organizations face: starting a skill library from scratch. This tool leverages AI to analyse job role data and automatically suggests a relevant skills library, making it easier for organizations to initiate their journey with the Talent Intelligence Hub.

Key Points:
- Automated Skill Mapping: The tool focuses on job role description fields to determine necessary skills, streamlining the process of building a comprehensive skills library.
- AI Unit Requirement: Access to this feature requires licensed AI units, ensuring that only premium users benefit from this advanced capability.
- Industry-Specific Insights: Initially supporting a range of industries like software, manufacturing, and general business, SAP plans to expand its coverage, enhancing the tool's relevance across more sectors.

NextGen Career Development: Integrated and Intuitive

The integration of the Growth Portfolio with Career Development and the Opportunity Marketplace is a significant enhancement. It brings a holistic view of career opportunities directly within the Growth Portfolio, enabling users to see targeted roles, understand skill gaps, and access role-readiness assessments seamlessly.

Enhancements Include:
- Role and Opportunity Insights: Direct integration allows users to view role-specific insights and growth opportunities without navigating away from their current workflow.
- Opportunity Marketplace Integration: Users with access to the Opportunity Marketplace will see tailored recommendations, further personalizing their development experience.

In one of the sessions last year at SuccessConnect, the SAP Product managers mentioned that a user shouldn't need to go to a module to access information. Any SF module should present the right information to the user in the screen that they are in - this seems to bring that to life!

Streamlining Upgrades with New Tools

Upgrading from Centre of Capabilities to Growth Portfolio still remains a challenging process for many. The latest release introduces new tools and functionalities to ease this transition:
- Check Tool Updates: New tools address common upgrade issues, such as invalid skills and competencies and job family mismatches in the Job Description Manager, offering quick fixes to streamline the upgrade process.
- Enhanced Reporting Capabilities: This release also expands the reporting functionalities, allowing users to export competencies and skills from the Talent Intelligence Hub for enhanced data analysis and decision-making.

Report Stories

With this release, you can now export the Competencies and Skills available for reporting in conjunction with Job Profile Builder data, so we can report on all skills and
competencies mapped to specific roles

The 1H 2024 release of SAP SuccessFactors marks a significant step forward towards management of talent, leveraging advanced AI technologies and integration to enhance user experience and organizational efficiency. These tools will help organizations with a speedier path to a skills based organizations. As SAP continues to evolve, these enhancements are set to offer organizations the tools they need to thrive in an increasingly competitive business landscape.

Getting down to business with AI: Step-by-step video tutorials

2024-04-29T10:56:09.993000+02:00

AI is revolutionizing businesses by transforming the way they operate, make decisions, and interact with customers. With its ability to analyze vast amounts of data, AI enables you to gain valuable insights and make more informed decisions by automate repetitive tasks, improving efficiency, and upleveling productivity. Generative AI, specifically, enables completely new capabilities in business software, such as creating new content, summarizing complex information, writing computer code, reasoning through problems, and more.

Did you know that AI already exists in most of your SAP solutions? AI is already a central, integrated capability of our enterprise applications and business technology, used by tens of thousands of our cloud customers.

Learn how to activate and configure AI capabilities across your business with step-by-step video tutorials.

Source, Engage, and Hire the Right Talent with Agility

By shifting the focus from job titles and degrees to a comprehensive understanding of employees’ skills, businesses can have a more accurate and efficient evaluation of talent across all levels. With the AI-assisted interview question generation and job description enhancement functionalities in SAP SuccessFactors solutions, recruiters can now generate an enhanced job description and interview questions using the power of generative AI. In this episode of Getting Down to Business with AI, we'll take you through enabling the AI-assisted Content Generator in SAP SuccessFactors, configuring the job requisition fields, setting up the integration between SAP SuccessFactors and Microsoft 365, and enabling the interview alerts and assessment in Microsoft Teams

Watch the video >

Quickly Resolve Finance Issues Before Payments

Adding intelligent technology to the auditing process allows your team to review expenses more efficiently and reimburse employees faster. With greater visibility into spending, auditors can also hold employees accountable and resolve spending discrepancies before they become problems. SAP Concur solutions use AI to enhance and automate processes, give auditors more visibility into spending, and protect your company’s bottom line. In this episode of Getting Down to Business with AI, we’ll take you through the configuration of AI in Verify, SAP Concur’s intelligent technology solution that streamlines processes, provides visibility into spending, and helps auditors to be more agile. Verify uses AI to analyze each item in expense reports and performs a series of checks for receipt and policy violations.

Watch the video >

Optimize Customer Relevance and Business Impact

Intelligent selling service is a technology-driven approach to sales that leverages AI to automate and optimize sales processes. It improves product discovery and increases brand engagement, drives conversion rates and raises average order value, and increases customer satisfaction and loyalty. The AI-based Intelligent Selling Services for the SAP Commerce Cloud solution captures and analyzes behavioral data in real-time across each customer’s commerce journey to create individualized customer experiences, which are optimized for both customer relevance and business impact. In this episode of Getting Down to Business with AI, we'll take you through the configuration of AI-based selling services, how to validate the foundation and merchandising modules, introduce tracking to the storefront, define product mix and strategy, and insert the strategy in the shop page templates.

Watch the video >

Tailor Recommendations, Save Costs, and Maintain Compliance with Guided Buying

Giving employees a personalized, guided experience when making purchases on the job allows users to save their company costs, stay compliant with organizational policies, and expedite the entire procurement process. In this episode of Getting Down to Business with AI, we’ll walk through the configuration of the AI capabilities within SAP Ariba Guided Buying AI, where you can deliver item recommendations that are tailored, cost effective, and compliant. You’ll learn about setting up and managing parameters, and quantity requirements for recommendations and usage reports.

Watch the video >

Increasing Productivity and Product Quality

Today’s manufacturing companies are not only looking to improve their overall first-pass yields and quality, but to also support continuous improvement programs that exist at the manufacturing-level. It’s not just about correcting things in line with the process, but how can larger corrective actions and workflows be applied around this process. AI-based Visual Inspection in SAP Digital Manufacturing is a feature that every manufacturing company is looking for. In this episode of Getting Down to Business with AI, we’ll take you through the configuration of Visual Inspection, the AI-based solution that defect detection to increase productivity on the shop floor, ensures product quality, and provides immediate added value for manufacturing companies.

Watch the video >

Gain Confidence, Speed, and Agility with Intelligent Product Recommendations

Manufacturers of complex configurable products often rely on the expertise of sales personnel to recommend the suitable product offering to their customers. This approach can be difficult to scale and result in a subpar buying experience for customers. In this episode of Getting Down to Business with AI, we’ll walk you through setting up the AI capabilities in SAP Industry Cloud with Intelligent Product Recommendations. You can recommend the optimal product (configurable or standard) and default configuration along with commercial attributes, such as lead time and price.

Watch the video >

SAP gives customers AI capabilities embedded into SAP applications, empowering their business processes with AI that's as intuitive as it is flexible and powerful. Our Business AI capabilities enable smarter decisions and efficiencies at scale, while our unwavering commitment to responsibility ensures trust and compliance in every interaction.

Interested in learning more?

Elevate Your Business with AI at SAP Sapphire 2024 Orlando!

2024-05-01T18:59:13.147000+02:00

Unleash the Power of Business AI

In an era where digital transformation is reshaping industries, Business AI stands at the forefront of innovation, driving efficiency, enhancing customer experiences, and unlocking new possibilities for businesses worldwide. SAP Sapphire 2024 in Orlando from June 3-5, 2024, offers a unique opportunity to explore the transformative potential of Business AI and connect with leading experts in the field.

Spotlight on Business AI: Don't Miss These Must-Attend Sessions!

Session 1: Translating Generative AI and LLMs into Business Benefits (SER207)
Unlock the future of our customer support offerings by exploring how generative AI and large language models (LLMs) help engineers support customers with outstanding speed. Delve into the design, implementation, and integration of LLMs for enhanced internal efficiencies. Elevate your support capabilities for an accelerated customer experience.
Session 2: AI in Customer Support: SAP's Path to Excellence (ASUG307)
Discover SAP's approach to support excellence by infusing AI into customer support, enhancing efficiency, and user satisfaction. Gain insights into actionable tactics for seamless AI integration and effective measurement of its business outcomes. Explore SAP's blueprint for top-tier AI-driven customer support.
Session 3: SAP runs SAP: Leading the AI Revolution in Customer Support (SER242)
Experience our AI-driven customer support paradigm. Uncover strategies for AI fusion, elevating support efficacy, and customer satisfaction. Witness our journey, which sets benchmarks for AI-powered customer service excellence. Use this blueprint to smoothly integrate AI into your company, unlocking success through the SAP for Me portal.
Session 4: Reinventing Support with AI (SER202+SER247)
Learn how our support offerings use intelligent automation and AI to elevate your customer experience. Gain insights into bi-directional support and witness our transformative journey toward delivering outstanding value. Step into the future of predictive, bi-directional support and maximize your support experience.

Experience Business AI in Action at SAP Sapphire 2024 Orlando!

Visit our demo station within the Services and Support Center on the show floor to see Business AI in action! Experience live demonstrations showcasing the power of AI in customer support, elevating efficiency, and user satisfaction. Uncover actionable strategies for effortlessly integrating AI into your operations and measuring its impact on business outcomes.

Exclusive Opportunity for 1:1 Meetings with Business AI Experts!

Don't miss the chance to engage directly with our Business AI experts during SAP Sapphire 2024! We're offering limited opportunities for 1:1 meetings at the Services and Support Center on the show floor in Orlando.

Limited Availability!
Take advantage of this unique opportunity to discuss your specific challenges and explore tailored solutions with our experts. Secure your 1:1 appointment now before slots fill up!

Request your meeting here: 👉I want to talk Business AI at SAP Sapphire 2024 Orlando

Get Ready to Elevate Your Business AI Strategy!

Join us at SAP Sapphire 2024 in Orlando to discover the power of Business AI and how it can transform your business operations. Engage with industry leaders, attend insightful sessions, and take the first step towards building a future-ready, efficient, and resilient business.

We look forward to seeing you there!

Feel free to share this article to promote the Business AI sessions at SAP Sapphire 2024 Orlando and encourage your network to arrange 1:1 meetings with our experts!

It's never been easier to invoke Machine Learning and Generative AI from an ABAP application

2024-05-03T08:34:43.224000+02:00

We have exciting news for SAP developers! You may remember that last year, IBM and SAP jointly announced a milestone collaboration around embedding AI into SAP solutions. One visible outcome was the adoption of Watson technology in the SAP Start and SAP Joule digital assistants.

And at the same time, IBM's been working on creating a watsonx Software Development toolKit (SDK) for SAP ABAP, complementing the existing Watson SDK that was refreshed in 2023.

I am pleased to confirm that the watsonx ABAP SDK version 1.0.0 is now live. It was released late March 2024 by the IBM SAP Software Engineering Team as expected. It is a separate release from its relative, the Watson SDK, who released a version 2 in Q4 2023. Both SDKs are open source and downloadable from GitHub.

If you develop SAP apps or have clients doing so, this is big news. It is truly a revolution in easily integrating Machine Learning and Generative AI, in just a few clicks, into an SAP ABAP application. Literally in 10 minutes!

The watsonx SDK comes in two flavors, allowing SAP developers to easily access watsonx from an ABAP application in a traditional SAP NetWeaver environment, and also in the latest SAP Business Technology Platform (BTP):

The SDK natively supports both the watsonx.ai (V1) and the Watson Machine Learning (V4). To get developers up to speed quickly, comprehensive examples are included in both of the APIs' documentation.

The sample code for the watsonx.ai sends a AI prompt to a generative AI model and collects the generated response. It uses the granite-13b-chat-v2 in the example but there are many other superb models available through watsonx.
The sample code for the Watson Machine Learning API lets you unleash the full capability of Watson Machine Learning (ML):
- Without going too far in the detail, to use watsonx ML you have to create a watsonx deployment space. This is where you will deploy your ML assets, which can be models, functions, or scripts.
- Python is a popular language for functions, in fact most frameworks in Watson ML rely on Python (or R). With a Python function, you can perform any ML task like creating, training, and using models.
  - For instance you can recognize hand-written digits, or to predict business area for a car rental company, etc.
  - You're welcome to write your own Python functions from scratch but in most cases you'd want to leverage existing example notebooks to save time
- Going back to the watsonx ABAP SDK: in the supplied sample code, the ABAP application deploys arbitrary Python code as a Python function on a watsonx deployment space and calls the deployed function. It also supplies a CURL command that can be used to easily call the deployed function from the command line
- So the SDK connects lets you use the full capabilities of watsonx ML with very little development effort. Then no further SAP programming knowledge is necessary, you can refer to the regular watsonx ML documentation. And of course, reuse the many examples of functions, models, and scripts provided by IBM and third parties.

See also the post by @christian_bartels on the same topic.

How to create LLM based Chatbot for SAP HANA Cloud using RAG Application

2024-05-06T05:51:47.618000+02:00

What is a RAG application?

RAG (Retrieval Augmented Generation) is like giving a super-smart robot access to a huge library of books (In our example it is SAP HANA Vector Engine) so it can find the right answers when you ask it questions. It works by blending two methods: one where the robot searches for information, and another where it generates answers. This way, the robot can understand your questions better and give you more accurate responses. It's like having a really knowledgeable friend who always has the perfect answer to your questions because they know where to look for information.

Objective

To create a quick and easy RAG application that can query SAP HANA Cloud Vector Engine using LLM and reply back as professional salesman. Below are the summary of tasks:

Create a table with a vector column, load the table with data
Call LLM with prompt and get an answer based on query
Fun with prompt engineering and the LLM chatbot!

Tools and Infrastructure needed

Since this is meant to be quick and easy, I would recommend below tools:

SAP HANA Cloud

This is available in SAP BTP Trial account here. Create an instance of SAP HANA Cloud - use Set Up SAP HANA Cloud Administration Tools - Boosters to speed up the setup process. Once the instance is up and running, change the configuration to allow all IP addresses to your instance at SAP HANA Cloud Central -> All Instances -> Click on HANA Cloud Instance -> Manage Configuration -> Connections Tab -> Make sure Allow all IP addresses is selected. This step will allow to reach SAP HANA Cloud from a client or another tool like a python notebook.

Visual Studio Code with Jyupter notebook extension

Download VS Code from here and Jupyter extension from here. Make sure latest version of python is installed.

Dataset from Kaggle

Download Amazon products CSV file from here.

API Key from OpenAI

Create an API key from here.

Exercise

Open SAP HANA Database Explorer and execute below query to create a table - PRODUCTS.

CREATE COLUMN TABLE "DBADMIN"."PRODUCTS"(
	"ASIN" NVARCHAR(50),
	"TITLE" NVARCHAR(1000),
	"IMGURL" NVARCHAR(500),
	"PRODUCTURL" NVARCHAR(500),
	"STARS" DECIMAL(3, 2),
	"REVIEWS" INTEGER,
	"PRICE" DECIMAL(10, 2),
	"LISTPRICE" DECIMAL(10, 2),
	"CATEGORY_ID" INTEGER,
	"ISBESTSELLER" BOOLEAN,
	"BOUGHTINLASTMONTH" INTEGER,
	PRIMARY KEY(
		"ASIN"
	)
)
UNLOAD PRIORITY 5 AUTO MERGE;

Right click on the table name and choose Import data from context menu. In the wizard like screen, provide the Amazon Products CSV file downloaded from Kaggle and upload the records to the table.

Execute below SQL to add two new columns - VECTOR_STR and VECTOR to the PRODUCTS table:

ALTER TABLE products
ADD (vector_str NCLOB,
     vector real_vector);

The setup of our datasource is now complete. Next step is to add text embeddings to one of the new columns - VECTOR_STR. These text embeddings are vector representations of the data - in this case it is the TITLE column. These text embeddings are created with the help of trained model, some choices are as below:

GPT-3 (text-embedding-ada-002)
MPNET (all-mpnet-base-v2)
Word2Vec (word2vec-google-news-300)
Glove (en_core_web_lg)

While all of them are great for general usage, since this tutorial is based on OpenAI hence GPT-3 is chosen as the embedding model. To add text embeddings, execute below python code:

%pip install hana_ml
from hana_ml import ConnectionContext

cc= ConnectionContext(
    address='<tenant-name>.hana.trial-us10.hanacloud.ondemand.com',
    port='443',
    user='DBADMIN',
    password='*****',
    encrypt=True
    )
print(cc.hana_version())
print(cc.get_current_schema())

import requests # type: ignore
import json
def get_text_embedding(text):
  url = "https://api.openai.com/v1/embeddings"
  headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer {}".format("***OpenAI Token here***")
  }
  data = {
    "input": text,
    "model": "text-embedding-3-small"
  }
  response = requests.post(url, headers=headers, data=json.dumps(data))
  if response.status_code == 200:
    return response.json()["data"][0]["embedding"]
  else:
    raise Exception("Error:", response.status_code, response.text)

def process_row(row):
    # Perform operations on each row
    # Uncomment below to see how embeddings look like - this will slow down the proecessing since it will print the vectors for each and every row
    #print(row['CATEGORY_NAME'],get_text_embedding(row['TITLE']))
    cursor1 = cc.connection.cursor()
    sql1 = """UPDATE PRODUCTS SET VECTOR_STR = '{}' WHERE asin = '{}'""".format(get_text_embedding(row['TITLE']),row['ASIN'])

    cursor1.execute(sql1)

cursor = cc.connection.cursor()
sql = '''SELECT * FROM PRODUCTS LIMIT 5000;'''
cursor.execute(sql)
hdf = cc.sql(sql)
df_context = hdf.head(5000).collect()
df_context.apply(process_row, axis=1)
#print(df_context)
cursor.close()

Visit this github link to download the Jupyter notebook for detailed explanations.

Now execute below SQL to convert all vectors into real vectors and populate the VECTOR column. This step will enable SAP HANA Cloud Vector Engine to execute similarity searches.

UPDATE PRODUCTS SET VECTOR = TO_REAL_VECTOR(VECTOR_STR);

Define below functions in python:

Function to perform vector search accepting parameters - query as string, metric can be either COSINE_SIMILARITY or L2DISTANCE and k is number of records:

def run_vector_search(query: str, metric="COSINE_SIMILARITY", k=4):
    if metric == 'L2DISTANCE':
        sort = 'ASC'
    else:
        sort = 'DESC'
    query_vector = get_text_embedding(query)
    sql = '''SELECT TOP {k} "ASIN", "TITLE" 
        FROM "PRODUCTS"
        ORDER BY "{metric}"("VECTOR", TO_REAL_VECTOR('{qv}')) {sort}'''.format(k=k, metric=metric, qv=query_vector, sort=sort)
    hdf = cc.sql(sql)
    df_context = hdf.head(k).collect()
    return df_context

Function llm_query that will perform ask LLM chatbot and perform human like conversations - not quite ready for a real conversation but the answer will be very well articulated:

def llm_query(query: str):
    from langchain_core.output_parsers import StrOutputParser # type: ignore
    from langchain_core.prompts import ChatPromptTemplate # type: ignore
    
    # Toggle and uncomment below prompt templates to execute use cases for with and without role
    
    # Use Case 1 - without LLM role assignment
    #promptTemplate = ChatPromptTemplate.from_template('''Context:{context} Question:{query}''')
    
    # Use Case 2 - with LLM role assignment as salesman
    promptTemplate = ChatPromptTemplate.from_template('''You are a salesman who promotes and sells online products. When pitching for the product, clearly mention the brand names, 
                                            it's multiple uses, benefits and cost - include a 10% discount if buying today. Use the following pieces of context to answer 
                                            the question at the end. Context:{context} Question:{query}''')
    df_vectorcontext = run_vector_search(query)
    context =  ' '.join(df_vectorcontext['TITLE'].astype('string'))
    #print(context)
    prompt = promptTemplate.format(query=query, context=context)
    response = model.invoke(prompt).content
    return (response)

Let us define below function such that it will take a query and print responses both from similarity search and LLM answer:

import textwrap
iWidth = 80
def print_responses(query: str):
    print("Results of query '" + query + "' for vector search:\n")
    df = run_vector_search(query=query)
    print(df.head())
    print("\nResults of query '" + query + "' from LLM:\n")
    print(llm_query(query=query))

Now let us test a few queries to compare the vector engine similarity search results versus LLM based conversation results.

Use Case 1

Uncomment below line and comment out the other prompt template that gives the salesman role to LLM:

promptTemplate = ChatPromptTemplate.from_template('''Context:{context} Question:{query}''')

Check below responses for each of the queries:

#Query 1 - plain keyword search
print_responses(query="electronics")

Results of query 'electronics' for vector search:

         ASIN                                              TITLE
0  B09V3DH4G9  DC 12V Electronic DC Buzzer 5v Alarm Active Pi...
1  B08G518BHN  DC 3-24V Active Piezo Buzzer 85 db with Indust...
2  B01MYPZZ19  IQ Toys-AB A+B Test Mind Game Brain Teaser Wir...
3  B0C7CNKGTT  cssopenss 6 Pieces Pocket Screwdriver Mini Top...

Results of query 'electronics' from LLM:

Which product is a mind game?

#Query 2 - phrase search
print_responses(query="electronics entertainment devices")

Results of query 'electronics entertainment devices' for vector search:

         ASIN                                              TITLE
0  B09V3DH4G9  DC 12V Electronic DC Buzzer 5v Alarm Active Pi...
1  B0057PLN9K  New Remote Control VR15-0980-0306-0302 Fit for...
2  B091699Z3W  Kasa Smart Plug Ultra Mini 15A, Smart Home Wi-...
3  B01BGUX78E  Ceptics 2 USB Israel Travel Adapter 4 in 1 Pow...

Results of query 'electronics entertainment devices' from LLM:

1. Kasa Smart Plug Ultra Mini 15A, Smart Home Wi-Fi Outlet Works with Alexa, Google Home & IFTTT: This device allows you to control your home's electronics from anywhere using your smartphone, making your home smarter and more efficient. 

2. New Remote Control VR15-0980-0306-0302 Fit for VIZIO LCD LED TV: This is a replacement remote control for VIZIO LCD LED TVs, which helps you to control your television from a distance effortlessly.

3. Ceptics 2 USB Israel Travel Adapter 4 in 1 Power Plug (Type H) - Universal Socket: This device allows you to charge your electronics while traveling internationally, particularly to Israel. This multi-device charger is compatible with most devices, making it a handy travel accessory. 

4. DC 12V Electronic DC Buzzer 5v Alarm Active Piezo Beep Sound ABS Housing 85dB Wired Connector Black 26Pcs: This device is an electronic buzzer that produces a loud beep sound when activated. It can be used in a variety of applications, including alarms, timers, and notifications.

#Query 3 - Popularity search
print_responses(query="What are top 10 electronics entertainment devices?")

Results of query 'What are top 10 electronics entertainment devices?' for vector search:

         ASIN                                              TITLE
0  B08798HG7F  Stylus Pens for Touch Screens, StylusHome 10 P...
1  B0BQD2TZSL                  Men's Top Ten Hi Basketball Shoes
2  B07C87CX9T  10 Plagues Passover Finger Puppets Vinyl Gift ...
3  B07L5RVRR2  T Shirt Boys Creeper Inside Black Short Sleeve...

Results of query 'What are top 10 electronics entertainment devices?' from LLM:

As an AI, I don't have real-time data, but as per common trends and popularity, the top 10 electronics entertainment devices might be:

1. Apple iPad Pro
2. Samsung Galaxy Tablet
3. Microsoft Xbox Series X
4. Sony PlayStation 5
5. Amazon Kindle Paperwhite
6. Apple iPhone 13 Pro
7. Samsung Galaxy S21
8. Apple AirPods Pro
9. Nintendo Switch
10. Oculus Quest 2 VR Headset. 

Please note that the list can vary based on personal preferences and the specific types of entertainment someone is interested in.

#Query 4 - Question that needs semantic knowledge
print_responses(query="Which items do you recommend for my dental needs?")

Results of query 'Which items do you recommend for my dental needs?' for vector search:

         ASIN                                              TITLE
0  B07PNPSZ18  Easyinsmile Dental Tofflemire Matrices Bands S...
1  B0BX9KQWDK  315 Count Floss Threaders for Braces, Dental F...
2  B07NPBY16M  RADIUS Toothbrush Source Floss Brush BPA Free ...
3  B00JVF4UZ6  Tenders Pre-Toothbrush, 12 Individually Packag...

Results of query 'Which items do you recommend for my dental needs?' from LLM:

AI: As an AI, I don't have personal experiences, but I can provide information based on general dental care. All the items you mentioned could be beneficial depending on your specific dental needs. 

1. Easyinsmile Dental Tofflemire Matrices Bands: These are typically used by dentists for restorative procedures. Unless you're a dental professional, you probably won't need these.

2. 315 Count Floss Threaders for Braces, Bridges, and Implants: If you have braces, bridges, or implants, floss threaders can be extremely helpful in maintaining your oral hygiene.

3. RADIUS Toothbrush Source Floss Brush: This appears to be a high-quality, eco-friendly toothbrush. Regular brushing is crucial for everyone's oral health.

4. Tenders Pre-Toothbrush: This product seems to be designed for babies who are teething or for individuals who have difficulty using a regular toothbrush. 

Without knowing your specific dental needs, it's hard to make a specific recommendation. However, generally, a good toothbrush and floss (or floss threaders if needed) are essential for everyone's dental hygiene routine. You should consult with your dentist for personalized advice.

Use Case 2

Uncomment below line and comment out the other prompt template that has only context and query:

promptTemplate = ChatPromptTemplate.from_template('''You are a salesman who promotes and sells online products. When pitching for the product, clearly mention the brand names, 
                                            it's multiple uses, benefits and cost - include a 10% discount if buying today. Use the following pieces of context to answer 
                                            the question at the end. Context:{context} Question:{query}''')

Since only LLM prompt template has been modified, let us focus on output from LLM conversation for the four queries:

Query = "electronics"

Salesman: Ladies and Gentlemen, I bring you a collection of high-quality, versatile electronic products that will cater to all your needs. First, let's talk about the DC 12V Electronic DC Buzzer. This fantastic device, housed in durable ABS, emits a clear 85dB beep sound, perfect for alarms or alert systems. Wired and ready to connect, it's available in a pack of 26 for just $50. Purchase today, and you'll receive a 10% discount, making it only $45.

For those in the industrial sector, the DC 3-24V Active Piezo Buzzer is a must-have. With 85 dB of industrial audio inside and 2-wire leads, it serves as an efficient electric alarmer. You can get a pack of 10 for just $30, and with our special 10% off today, it's only $27!

Boost your brainpower with the IQ Toys-AB A+B Test Mind Game. This brain teaser wire magic trick toy IQ puzzle set is an excellent investment in your mental agility. Available in a pack of 16, this metallic set is only $20, but with today's discount, it's a steal at $18.

Last but not least, we have the cssopenss Pocket Screwdriver Mini Tops. These magnetic pocket screwdrivers come with a single blade head, perfect for mechanical or electrician work. In a striking green color and available in a pack of 6, these are priced at just $15. But with our exclusive 10% discount today, you can grab them for only $13.50.

Invest in these quality products and experience the benefits for yourself. Remember, the 10% discount is valid only for today. So, hurry up and grab these deals while they last!

Query = "electronics entertainment devices"

Salesman: Greetings! I have some exciting products in the electronics and entertainment devices sector that I'm sure you'll find interesting. 

Firstly, we have the DC 12V Electronic DC Buzzer. This high-quality buzzer comes with a 5v active piezo beep sound, ABS housing, and an 85dB wired connector. Its versatility means it can be used in various applications, such as alarms, timers, or even as a fun DIY electronic project component. Each pack containing 26 pieces costs just $20, and if you purchase it today, you can avail a 10% discount!

Next, we have the Remote Control VR15-0980-0306-0302, designed especially for VIZIO LCD LED TVs. This top-notch remote control is not only new but perfectly fits with various VIZIO TV models, making your TV viewing experience more convenient and enjoyable. It's available for only $15, and don't forget the 10% discount if you buy today!

Thirdly, we have the amazing Kasa Smart Plug Ultra Mini 15A. This smart home Wi-Fi outlet works with Alexa, Google Home & IFTTT without requiring any hub. It's UL certified and works with 2.4G WiFi only, thus ensuring your home automation is easy and secure. Priced at $10 for a 1-pack, this is a steal, especially with the 10% off today!

Lastly, we have the Ceptics 2 USB Israel Travel Adapter 4 in 1 Power Plug (Type H). This universal socket is perfect for your travel needs, allowing you to charge multiple devices simultaneously, no matter where you are. For just $25, and with a 10% discount if you buy today, this is an absolute necessity for every traveler.

Don't miss out on these fantastic deals. Secure your products today and enjoy the discounts!

Query = "What are top 10 electronics entertainment devices?"

Salesman: Ladies and Gentlemen, I am here to introduce you to a number of fantastic products that will cater to your electronic and entertainment needs today. 

Firstly, let me present the StylusHome 10 Pack Mesh Fiber Tip Stylus Pens. These are ideal for touch screen devices, suitable for iPad, iPhone, Samsung tablets, and all precision capacitive universal touch screen devices. They provide precise control for selecting icons, writing, drawing and gaming. You can own this pack of 10 pens today for a discounted price of $27, a full 10% off from its usual price of $30. 

Next, we have the men's Top Ten Hi Basketball Shoes. These shoes are renowned for their excellent grip, comfort and durability, making them perfect for both casual wear and intense basketball games. They are available today for just $90, a 10% discount from the regular price of $100. 

Lastly, I'd like to introduce you to our 10 Plagues Passover Finger Puppets Vinyl Gift Box Set. This set is perfect for Passover celebrations, offering hours of fun for kids and adults alike. The set includes 10 puppets each representing one of the Ten Plagues, making it a great tool for teaching and entertainment during the Jewish holiday. This set is available today for $18, a 10% discount from its regular price of $20. 

And, don't forget the T-Shirt Boys Creeper inside Black Short Sleeve Gamer Top suitable for 9-10 years old kids. This shirt features a cool and trendy gaming design, perfect for your little gamer. This shirt is available for just $9 today, a 10% discount from its usual price of $10. 

These are my top picks for electronic entertainment devices and more! Grab them today to avail the 10% discount!

Query = "Which items do you recommend for my dental needs?"

Salesman: Absolutely, I have some fantastic recommendations for your dental needs that not only contribute to healthy teeth and gums but also make your daily oral hygiene routine more efficient. 

First, we have the Easyinsmile Dental Tofflemire Matrices Bands. These are made of stainless steel and are excellent orthodontic supplies. With a thickness of 0.04 mm, you get 144 pieces in one pack. They greatly assist in achieving optimal contour and tooth separation during dental procedures. They are a must-have for any individual who wants to maintain their dental braces effectively. 

Secondly, a pack of 315 Count Floss Threaders is available. This pack comes in green and contains nine packs in total. They are specifically designed for braces, bridges, and implants, making flossing in between and around your dental appliances a breeze. 

The third product is the RADIUS Toothbrush Source Floss Brush. This brush is BPA Free & ADA Accepted. It's designed to improve gum health & reduce gum issues. The medium-sized, starch-based brush is perfect for daily use, promoting overall dental health. 

Lastly, we have the Tenders Pre-Toothbrushes. These are ideal for individuals who need to gently clean their teeth or gums. You'll get 12 individually packaged pre-toothbrushes with a yellow trim in a pack. 

All these products are available online. If you decide to buy these products today, you'll receive a 10% discount on your total. 

The Easyinsmile Dental Tofflemire Matrices Bands are priced at $30, the 315 Count Floss Threaders at $15, RADIUS Toothbrush Source Floss Brush at $10, and the Tenders Pre-Toothbrushes at $8. With today's discount, you'll be able to get all these for a total of $56.70 instead of the regular price of $63. 

Remember, investing in your dental health today will save you from potential dental issues tomorrow.

Conclusion

It is clear from these experiments how valuable an LLM conversation can be but again it depends on how prompt template has been designed.

In the first use case, LLM doesn't have any role or motive - it is just give a few keywords to come up with something that it just makes up. Hence in the very first query it just throws a question - "which product is a mind game?".
In the second query, the LLM gets a few more inputs when the query becomes very specific by describing electronics under entertainment. Hence it goes on to describe each of the items.
However, the search result become interesting when the question is asked - what are the top 10 electronics entertainment devices. In this case, the vector engine does similarity search and finds the keywords "top" and "10" and returns the results. But LLM understands the context and ignores this list, instead it comes up with it's own top 10 list. This is very classical case of hallucination but at the same time it can seem very relevant because these items were never provided to LLM by vector engine(examine the list returned by vector engine).
The fourth query gives even more interesting results when vector engine just returns list of dental products but ignores the specific needs of the user! But LLM takes it one step forward and puts a disclaimer while listing and describing each of the products and specific situations when they can be used.
In the next use case, the role of a salesman is assigned to LLM. For the first query, while vector engine just returns the top matching similar and relevant items, LLM adds a new dimension by putting an elevator pitch for those products, adding neat descriptions, even assigning a price and then a discount - this is a clear case of hallucination but may seem relevant because vector engine never provided price information.
LLM output is similar for phrase search as well, notice the similarity in sales pitch and hallucination in this case as well
For the query - what are the top 10 electronics entertainment devices, this becomes funny when vector engine returns products with keywords "top" and "10" and LLM takes one step further and adds elevator pitch for them. The first item is even okay but second one is basketball shoes, third one is finger puppets and fourth one is boys short sleeve t-shirts - none of them having any resemblance to electronics! Now LLM is indeed acting as salesman!
The last query for recommending items for dental needs - the LLM acting as salesman now removes all disclaimers and ready to sell the list provided by vector engine. Again, it assigns prices and discounts on it's own and ends it's dialog with an action item - "Remember, investing in your dental health today will save you from potential dental issues tomorrow."

SAP HANA Cloud Artificial Intelligence

10+ ways to reshape your SAP landscape with SAP Business Technology Platform – Blog 7

2024-05-06T09:21:24.167000+02:00

Blog 7: The Role of Automation for Transformation Projects

In times of constant change, quickly emerging demands for digitalization and competitive markets, companies are looking for ways to further optimize their processes. Consequently, many organizations have turned to automation technologies, such as RPA tools, to automate mundane and repetitive tasks. The benefits of automation are quite obvious: Automated processes are faster, less prone to error and people can concentrate on more complex, higher value-added activities.

Especially for activities with high volumes the benefits can be huge. Let me illustrate this with an example: A few weeks ago, I talked to a company from the consumer products industry. While a lot of transactions with its suppliers run fully digital via B2B integration, they still receive roughly 4.000 documents per month such as invoices and purchase orders via email. Let us assume you need on average 2 minutes for processing one document, that is: Extracting and verifying the data, collecting approvals, creating it in the ERP system and so on. In total, this sums up to over 130 hours of manual work per month. Applying RPA tooling and AI for document understanding can drastically speed up the processing of these tasks, thereby freeing people from tedious copy & paste or data entry and export activities.

Why looking at automation only is not enough

To streamline their processes, many companies have also started looking into other technologies: Besides RPA, also workflow engines, integration middleware as well as tools for process mining and process analytics have risen. One big downside is that these technologies often are not well integrated and hence customers are struggling with setting up an aligned end-to-end approach.

With our Enterprise Automation offering we want to address this and provide a unified and interlinked approach. As described in the blog article by Angela Harvey, this concept is based on the combination of 3 products:

SAP Integration Suite: You cannot automate what you can’t connect to. Our suite provides unparalleled connectivity and integration for a variety of scenarios. Be it SAP / Non-SAP, Cloud / on-Premise applications, B2B, B2G, API-led or event-driven scenarios.
SAP Signavio: Before you optimize, you might need to understand where to start and uncover inefficiencies first. With SAP Signavio you can analyze, model and govern your business processes to drive operational change.
SAP Build: Drive automation of long-running processes with capabilities for app development, process automation and portal sites. Low-Code/No-Code and visual design tooling also empower citizen developers and business experts to contribute to the development process in an agile fashion.

It is important to note that Enterprise Automation is a flexible and modular concept. Hence, customers can start with whatever product they see fit. From a transformation perspective Enterprise Automation can provide significant benefits when modernizing your SAP ERP, so when moving from the classic SAP Business Suite to SAP S/4HANA. It can be applied at any stage, both before the migration as well as after the migration:

Before the move: Leverage Signavio’s “plug and gain” approach and LeanIX to analyze and clean up processes in advance and gain immediate benefits from applying automation (e.g. via pre-built content packages). Use the Integration Solution Advisory Methodology of the SAP Integration Suite to design and prepare a future-proof integration strategy.
After the move: Bring process excellence to the next level by combining process mining, integration and automation and enable a continuous improvement cycle. Enable a governed approach to accelerate and scale the building of process automations based on Low-Code/No-Code techniques.

Another advantage in terms of transformation is the versatility – similar to a Swiss Army Knife. Enterprise Automation allows process optimization across the enterprise and line of businesses: Be it sales, procurement, HR, finance, production or logistics. A comprehensive collection of use cases and end-to-end scenarios has been put together by Manuel Namyslo in his blog article: How to get started with Enterprise Automation.

The role of AI in Enterprise Automation

Let us take a closer look at the role of AI and how it fits into the picture of Enterprise Automation. When transforming business processes and modernizing enterprise applications, AI should be part of the agenda, due to the massive benefits it can provide. Within our Enterprise Automation offering, the AI capabilities are tightly embedded to make the consumption as easy, seamless and relevant as possible.

A few highlights of them include:

Use Document Information Extraction (DOX) within SAP Build Process Automation to grab data from documents like invoices, payment advices and purchase orders to automate their processing. We also plan to integrate the DOX premium edition to make the processing of arbitrary documents with varying structure and layout even simpler.
We plan to use AI to provide recommendations for workflows as proposals based on historic data. This will support and speed up the decision making for approvals and workflow items (see roadmap item).
Visual tools already cater towards ease-of-use and simplify the building of process automations by business experts. There are also plans to make the design process even more intuitive by leveraging Generative AI functions (see corresponding roadmap items). As illustrated in this preview video, users describe what they need or what they want to craft in natural language. This can be an entire process flow, but also single process steps such as a business rule. The system then automatically generates the respective building blocks. Apart from that the AI-based assistant will also help with the discovery of pre-built content by providing suitable proposals from the content catalog.

As you can see AI is a crucial factor in many ways. Not only for the automation of processes, but also to accelerate the design and development process in various aspects. In addition, Enterprise Automation can also help with infusing AI into the process layer, by providing the respective integration capabilities.

To conclude: Enterprise Automation should be considered as a strategic tool set in the light of any transformation initiative for ERP and enterprise application landscapes. Its modular style allows you to start small at any stage of your project: From simple workflow automation and high-level process modelling, up to a fully-fledged vehicle for continuous process excellence. While our offering is optimized for SAP applications and systems, we embrace openness and enable process excellence across heterogeneous IT landscapes.

Where to look next and where to start? I recommend checking out the blog article How to get started with Enterprise Automation to get further inspiration. In addition, Low-Code/No-Code tooling such as SAP Build is well suited for getting Hands-On experience. Therefore, feel free to reach out to your SAP account manager to experience the ease-of-use in a Hands-On workshop. Finally, start by looking into potential use cases and assess them with the help of SAP or partners on how to tackle them with Enterprise Automation.

Previous Blogs:

Blog 1: The Central Role of Clean Core and AI
Blog 2: The Role of BTP as Extension and Innovation Platform
Blog 3: How Clean Core can accelerate your SAP Business Transformation
Blog 4: Mastering the Data Dance: The Potential of Clean Core and AI
Blog 5: How hybrid Integration upholds the role of Clean Core
Blog 6: Clean Core Extensibility

Where I learn how AI technologies can be leveraged to address key challenges in finance?

2024-05-06T14:31:54.710000+02:00

We recommend to access our Discovering AI Capabilities for SAP Finance learning journey.

Overview
Delve into the cutting-edge intersection of finance and artificial intelligence (AI) with SAP’s innovative solutions. Gain a deep understanding of how SAP's AI strategy revolutionizes financial management, empowering organizations to make data-driven decisions and optimize business processes.

Learning objectives

Understand SAP's AI strategy and its implications for financial operations.
Explore the range of AI offerings within SAP that cater to finance functions.
Learn how AI technologies can be leveraged to address key challenges in finance.

Please ask a question related to the digital learning Journey in the Q&A area.

Our SAP Learning Experts will get back to you as soon as possible! We are here to support you.

We appreciate your feedback and we will make sure to continue sharing interesting topics.

1H 2024 the “Employee Experience” release

2024-05-07T09:24:30.259000+02:00

By now, you’re probably diving deep into the SAP SuccessFactors’ 1H 2024 release and you might have noticed that our attention is focused on none other than the employee. After all, we’re all an employee of one sort or another. We might be an individual contributor, a manager, a project lead, a department leader, an HR professional, or even a CEO. So, as we continue to invest in delivering the best user experience, we are happy to share what’s in store for every one of our customers’ employees, including you.

Everyone has a story to tell and so does your organization

People are the most important element in an organization’s success. Understanding who your co-workers are, what your employees bring to the team, and easily connecting individuals to one another is important for every organization. That’s why I’m pleased to highlight the new People Profile experience. With the 1H 2024 release, you’ll experience the new profile “Spotlight”. It focuses on enabling employees to easily share their strengths and value throughout the organization. With a focus on progressive discovery, the profile Spotlight facilitates deeper exploration, supported by the new Profile Preview that’s present across the solution. The addition, the new Profile Preview enhances contextual understanding by providing essential information about each employee, fostering better connections and collaboration. With a layout and card design optimized for rapid engagement and comprehension, the new People Profile experience not only elevates the employee experience but also strengthens organizational cohesion and knowledge sharing. Best of all, the new Profile Preview and Spotlight are coming to our iOS and Android apps, too.

In addition, our new Org Chart makes it easy for employees to explore key aspects of their organization. Seamlessly connecting employees to the new Spotlight feature, the new Org Chart helps individuals to understand at-a-glance, everyone’s place within the organization. A clean and crisp visual experience makes navigating the organizational structure and hierarchy super intuitive. Plus, the lightning-fast UI means employees can delve deeper to explore more in less time.

AI provides every employee a competitive advantage

Joule is a game-changer when it comes to helping employees be as productive as possible. With a host of self-service capabilities for employees and managers, Joule empowers employees to effortlessly do more. The copilot’s clean and clear visual language makes it easy to focus on the task at hand. It’s conversational design, fuzzy matching for less-than-perfect spellers, and 1-tap suggestive answers, make everyday tasks as quick and seamless as possible. Moreover, Joule extends across all SAP solutions so the experience of using it is consistent and familiar. As we look ahead, by leveraging LLM and and Retrieval-Augmented Generation (RAG), questions like “Is emergency room service covered in the medical plan?” or “We are about to announce quarterly results, can I sell company stock?”, will be answered and include links to source documentation building confidence and trust with your employees.

With our new AI-assisted Goal creation experience, we’re helping employees and managers to craft well-defined, actionable, and measurable goals. Powered by generative AI, this new feature swiftly transforms ideas into comprehensive goals ensuring alignment with the organization's strategy. The benefit is a significant reduction in the time required to create meaningful goals. Plus, pre-prompting promotes ease of use and encourages adoption. The solution’s simple yet effective results make achieving goals more tangible, while motivating employees to strive for success. In addition, AI-assisted writing functionality is incorporated in the Goals experience to enable further employee-led refinement of goals.

Our new AI-assisted writing tool elevates communication. Whether you're grappling with finding the right words or seeking to enhance the tone of your communication, AI is your trusted companion. The comprehensive editing functionality offers suggestive approaches to getting your message just right. The solution even enables contextualized editing. For example, this includes prompts to "make it actionable" when giving feedback and other forms of purpose-built support tailored to specific tasks. Looking ahead, the text analyzer feature promotes inclusivity by guiding users toward more inclusive word choices.

With this release we’ve also enhanced the Applicant Workbench with the introduction of a skills-based intelligent recruiting experience that redefines talent acquisition. Recognizing that skills are the currency of a modern economy and the foundation of talent decisions, this platform offers insightful and expansive consideration of every candidate and their skills, enabling recruiters to make better informed decisions. The skills layout accelerates the time to review candidates by prioritizing skill matches and even adjacent skills. Furthermore, AI explanations frame the results, so recruiters understand the sourcing methodology. This enhances transparency and trust in the recruitment process.

A new benefits enrollment experience is here

With this release I’m excited to share the introduction of a new Benefits Enrollment experience. Embracing a consumer-style shopping approach, this solution delivers a familiar and intuitive experience and enables employees to navigate the benefits selection process with ease. With step-by-step guidance, employees can make informed choices with the help of embedded content that provides valuable insight into benefits options. A running expense total enables employees to manage their spend as they progress through the enrollment process, ensuring transparency and control over their benefits selections. With this new Benefits Enrollment experience, employees gain the tools and support to make decisions that align with their needs and preferences.

Engage in the flow of work with SAP SuccessFactors for Microsoft Teams

The updated app is a groundbreaking new experience for SAP SuccessFactors within the Microsoft Teams application, designed to seamlessly bring HR directly into the flow of work. Anchored by a new homepage, this experience serves as a central hub, making navigation effortless. With today's collaboration tools enabling employees to complete HR related tasks within the flow of work, employees have even more opportunities to self-serve. For example, they can give and receive feedback in the moment, and stay on top of timely activities such as spot award approvals and learning requirements. This not only enhances employee engagement but also helps ensure that HR tasks are seamlessly managed as part of employees' daily routines. The clean and simple design makes discovery of tasks and to-do’s quick and easy.

The 1H 2024 release: something for everyone

By placing the employee at the center, this release empowers individuals across all levels of the organization, recognizing that everyone has a story to tell. From the redesigned People Profile and Org Chart, which facilitate deeper connections and collaboration, to Joule and the AI-assisted writing tool, which streamline processes and enhance productivity, each innovation improves engagement and efficiency. Furthermore, the integration of SAP SuccessFactors with Microsoft Teams and the revamped Benefits Enrollment experience demonstrate a commitment to meeting employees where they are and simplifying how they accomplish HR related tasks. As we continue to invest in enhancing the employee experience, we are not only fostering a more connected and engaged workforce but also driving organizational success and growth.

Expanding Proactive Solutions: Critical Content now Live in SAP for Me

2024-05-09T17:51:57.264000+02:00

What you already know:

What priority solutions is support currently working on that could prevent business impacting issues on your systems (Hot solutions).
What solutions, relevant for your systems are other customers viewing most today (Trending solutions).

What is new?

Relevant Critical content recommended by our product experts are now directly available for your product within the ‘Get Support’ app in SAP for Me!

As soon as you choose your Product and Product Function when creating a case, you get:

Awareness of anything critical for your business
Any workarounds or solutions available
Ability to subscribe to the critical content to follow for the latest updates

This ensures reduction in effort and time for you to resolve any issues causing severe business impact and ongoing updates providing latest solutions directly to you.

Where will you be notified?

Navigate to the Services & Support dashboard > ‘Get Support’ app in SAP for Me.

Fill in the Customer, Description, System, along with the relevant Product & Product Function fields.
If a critical solution exists for your Product or Product Function, you will be prompted with a popup outlining the relevant Critical KBA or Note linked with an option to subscribe.
It will also appear at the top of the right-hand side list of Recommended Solutions.

What to expect next?

We will continue to refine further which customers receive this popup in SAP for Me
We will push the notification of critical issues to further locations for customers to consume e.g., Built-In Support within the Product

Please also check out the below blog for more ways to access Proactive Solutions in SAP for Me!

Unlocking Proactive Solutions: Preventative Content now Live in SAP for Me

How Defense and Security Organizations can Easily Migrate to the Cloud with RISE with SAP

2024-05-10T12:58:55.515000+02:00

Figure 1: Example picture

1) Introduction

In the recent years, cloud computing has been among the most important IT trends, and it will continue to do so within the next decade. The leading technology consulting firm, Gartner, published various insightful statistics about the technology and its importance that highlight the importance for both private enterprises and public organizations. For one thing, as the below graph shows, the market for public cloud services will grow to $1 trillion by 2026. This relates to a growth rate of more than 100% when compared to the year 2021 and even marks the highest growth rate of all existing IT markets.

Figure 2: Forecast for public cloud services growth by Gartner

This strong trend towards cloud computing is also reflected in a Gartner survey among 367 enterprises . As you can see in the chart below, more than 50% of the survey participants in 2022 think that cloud technology is either indispensable or heavily impactful. When asked about the year 2027, even 90% believe that this will be the case.

Figure 3: Gartner cloud computing survey

Furthermore, 50% of surveyed organizations will use industry cloud platforms to accelerate their digital business initiatives in 2027, according to Gartner. In contrast, less than 5% of the participants gave this answer in 2022.

2) The Importance of Cloud Computing for the Defense and Security Industry

Cloud services are also of high importance for Defense and Security (D&S) organizations, like armed forces, aid organizations or emergency organizations. A recent study financed by the European Defense Agency shows that cloud computing can be applied to both the strategic level and the field level of military organizations. Furthermore, cloud technology can support European armed forces in achieving information superiority against its adversaries. The advantages of cloud technology apply to emergency organizations, like police forces, in a similar manner. Here cloud technology does not only improve the collaboration within and across police organizations, but also helps to complete criminal investigations faster. Fire departments can benefit from the technology as well. Examples for this include cost reductions, access to innovative IT services, a higher reliability of IT services or improved cybersecurity. Rescue service organizations, in turn, can profit from cloud computing through a better and faster handling of medical data. In this way, rescue chains in general and the planning of medical treatments can be improved significantly, which in the end can help to save people’s lives.

3) What is RISE with SAP?

Figure 4: Introductory video to RISE with SAP

RISE with SAP is a holistic package for customers, which want to transform their existing on-premises SAP systems into the cloud. RISE with SAP thereby not only includes SAP’s top-of-the-range software solution, SAP S/4HANA Cloud Private Edition, but also various connected services, such as, cloud infrastructure and security as well as related migration and modernization programs. Businesses and organizations, which are not yet SAP customers can instead use GROW with SAP. GROW with SAP is an offer, that is specifically designed for new customers and small and midsized companies and organizations. But let us now take a closer look what specifically RISE with SAP offers for existing customers.

Figure 5: RISE with SAP overview graphic

The RISE package generally makes system transformations easier and allows customers to profit from all of the latest innovations from SAP. The key components of RISE – as the above graphic shows – are:

1) Cloud Solutions

S/4HANA Cloud Private Edition allows you to optimize processes in an unprecedented way. The Cloud ERP solution in this regard covers all common business functions of Defense and Security organizations like, for instance, procurement, human resource management or military planning and operations. Additionally, RISE with SAP includes packages, like the SAP Business Technology Platform (BTP) for app development, data management, automation and real-time analytics and SAP Signavio for process mining. The RISE solution beyond this also includes diverse innovative and helpful SAP Business Artificial Intelligence functions and features, that allow your organization to get better insights and save valuable time and money. What is more, the RISE program enables D&S organizations to use our holistic sustainability software, SAP Sustainability Solutions. These solutions not only allow organizations to monitor and manage sustainability and environmental issues, but also to ensure the safety of their employees at their workplaces.

2) Cloud Infrastructure and Security

RISE with SAP is built on the foundation of state-of-the-art IT infrastructure and security. In this regard, our customers can benefit from a very modern cloud infrastructure, that helps to ensure the highest possible system performance and availability of services around the clock. Furthermore, D&S organizations can profit from simple and effective service level agreements (SLAs), that guarantee a 99.7% availability as well as regular maintenance of our SAP cloud solutions. Moreover, our RISE with SAP offering is based on the highest standards for security and data protection. This not only entails regular security updates, but also the ability of permanently monitoring the system with regards to performance, compliance and potential threats.

3) Migration and Modernization

Our RISE with SAP cloud package aims to make the migration from on-premises systems to modern cloud systems as simple as possible. SAP for this created an easy, guided implementation process, that is based on the SAP Activate methodology. This methodology allows our customers to:

Gain an in-depth understanding of the extensive capabilities of cloud ERP.
Receive expert guidance to strategically plan and prepare for a smooth migration.
Discover new avenues to craft detailed implementation plans across multiple workstreams.
Seamlessly progress through all six implementation stages with clarity and precision.
Tap into a vast partner ecosystem for enhanced support and collaboration.
Access comprehensive assistance, that is available in more than 100 countries worldwide.

4) The Key Advantages of RISE with SAP

RISE with SAP unites all advantages of cloud computing technology with the well-known advantages of SAP software solutions. The combination of the two technologies thereby even enabled SAP to create its most advanced ERP products so far, SAP S/4HANA Cloud Public Edition and SAP S/4HANA Cloud Private Edition. The main advantages of RISE with SAP are:

High scalability and usage-based pricing

Our cloud solutions allow your D&S organization to easily scale your SAP systems, in a needs-based manner. This is not limited to a certain part of your organization, but can be applied across your entire global operations. The high scalability thereby not only facilitates your organization’s IT processes, but also pays off financially due to the “pay only what you need approach”.

Better collaboration

SAP S/4HANA Cloud allows for a better collaboration among your workforce. Your employees are enabled to work jointly on tasks, communicate directly and share information. This can be done for instance with the SAP Signavio Process Collaboration Hub, a versatile tool for process collaboration. Furthermore, our cloud ERP solutions also enable our clients to better collaborate with their stakeholders, such as suppliers.

Process automatization and access to diverse innovative functions and features

The RISE with SAP offering entails access to various innovative platforms, functions, and features as well as to a variety of useful partner solutions. Examples for this are the SAP Business Technology Platform or SAP Business Artificial Intelligence, two solutions, that were designed to complement each other perfectly. The BTP, on the one hand, is a platform, that bundles services like data management and analytics, application development, automation, and integration as well as artificial intelligence in one environment. The platform is thereby also helping to accelerate the transformation to the cloud significantly. SAP Business AI, on the other hand, is an umbrella term for all available AI solutions from SAP. Good examples for this are SAP Joule, a Generative Artificial Intelligence-based copilot within SAP applications. SAP Joule can answer diverse questions, guide the user through the application or even solve various tasks in an automated manner. Other examples for SAP Business AI include the automatization of processes, such as guided buying or automatically generated job descriptions.

5) Migration Options

D&S organizations, which are already using SAP solutions and want to migrate their systems to the cloud can choose among two principal migration options:

1) Migrate from SAP ERP

D&S organizations, that use SAP ERP and want to migrate to the state-of-the-art SAP S/4HANA Cloud Private Edition can profit from a guided transformation process. This process allows the organizations to make use of diverse best practices for the migration of their systems and data throughout all phases of the transformation journey. Principal advantages of this concept are that customers are enabled to maintain system configurations just like their data sets easily in the new cloud environment.

2) Migrate from SAP S/4HANA

The migration from an existing on-premises SAP S/4HANA system to SAP S/4HANA Cloud Private Edition is even less complex. The transition to the cloud here works very frictionless, which means that – in most cases – customers can just transform their systems and data centers to the new S/4HANA Cloud Private Edition environment.

3) Alternative for new customers: GROW with SAP

As already mentioned above, SAP recommends new customers the tailored cloud transformation program GROW with SAP. GROW with SAP allows for a fast and predictable implementation of the SAP cloud systems and includes most of the advantages of the RISE offering. Unlike the RISE with SAP package, the GROW solution relies on a Public Cloud architecture in the form of SAP S/4HANA Cloud Public Edition.

6) Security Features of RISE with SAP

RISE with SAP is built on a comprehensive security architecture, that enables our customers not only to work safely, but also to protect their data regardless from where and in which local circumstance they work. The security architecture comprises enterprise-grade security features and standards, like:

Physical access control
User authentication and authorization functions
Advanced functions for the function and user-based separation of data
Data encryption
Automated back-ups and protection from data losses (data recovery)
Data encryption features
Full compliance with data protection guidelines like the General Data Protection Regulation (GDPR)

- Comprehensive protection of client data

- Auditing functions

- Integrated capabilities for deleting personal data

Sovereign Cloud solutions for organizations with higher security and data-protection requirements, including:

- Use of data centers, that are located in the resident country or region of the respective company or organization

- Data being solely stored and processed within the sovereign borders of the country or region

- Corresponding proof of national and international security certifications and attestations

- Adherence to high security standards throughout all steps

- Increased security requirements for employees

7) Cloud Solutions with Advanced Security Features by SAP NS2

For companies and organizations, which have even higher cybersecurity requirements, SAP is offering cloud solutions with advanced cyber security measures. SAP therefore established its own independent subsidiary called SAP National Security Services (SAP NS2). SAP NS2 is mainly focused on the US, Canadian and Australian market, where it, among other things, is responsible for the adherence of SAP products to diverse security and regulatory requirements. The focus of SAP NS2 thereby lies on ultra-secure cloud solutions for highly regulated industries like D&S organizations, but also for actors with such needs within other industries. This includes highest level of security standards, like the US Department of Defense Impact Level 4 (DoD IL4) requirements just like the US Federal Risk and Authorization Management Program (FedRAMP) certification. The company’s product portfolio includes:

SAP Secure Cloud Services and Products
- SAP NS2 offers a great range of SAP cloud products and solutions with enhanced security standards. The product portfolio includes ERP-solutions, like SAP S/4HANA, as well as diverse solutions for functional areas, like Supply Chain Management, Finance, Human Resource Management or Spend Management. In addition, NS2, with the SAP Business Technology Platform, also offers diverse automation, analytics, data management and Artificial Intelligence solutions.
Professional Services
- SAP NS2 offers its customers a variety of Professional Services, that range from cloud transformation over advisory services to implementation services.
Support
- SAP NS2 permanently supports its customers with a highly specialized customer service team, which answers any kinds of questions or issue resolution.
Mission Solutions
- SAP NS2 offers a variety of additional services under its brand DataCTRL, that allow D&S customers to securely manage and catalog data across their organization. DataCTRL thereby enables D&S organizations to perform a better and faster data handling, which, for instance, can speed up the migration from on-premises to cloud systems.

Key Takeaways

All in all, this blog entry has shown that RISE with SAP brings significant benefits for Defense and Security organizations, that shouldn’t be ignored. This includes advantages, such as, process automatization just like better collaboration or access to the latest functions and features. What the blog has also shown is that cloud technology, like RISE with SAP, can make all types of D&S organizations more efficient and successful, and here even allows them to strengthen themselves within their core competencies. Although the security of cloud solutions is typically a rather controversial issue among IT responsibles, it has been shown in the blog that SAP’s cloud solutions are built on the foundation of a strong security architecture. This architecture includes various security functions and features like automated backups, encryption, or access control functions. For organizations with even higher cybersecurity requirements, SAP can refer its customers to its specialized subsidiary, SAP NS2. SAP NS2 offers ultra-secure cloud solutions with the highest possible security certifications for highly regulated industries, like Defense and Security. Beyond that, our customers can expect numerous further innovations for the future from SAP, which includes Generative AI functions just like the stepwise integration of SAP’s intelligent copilot, Joule, into SAP applications.

Product Tour for SAP S/4HANA Cloud Private Edition

If you are interested in learning more about RISE with SAP and SAP S/4HANA Cloud Private Edition and its advantages for the different operational processes in the following product tour:

Figure 6: Link to the RISE with SAP product tour

Sources

Accelerate Digital Transformation, Enable Compliance, and Mitigate Risk with Sovereign Cloud Capabilities from SAP. (2023, September). SAP.

Breaking the cloud barrier in aerospace and defense. (2022). Accenture.

‘Combat cloud’: EDA study shows benefits of cloud computing for EU militaries. (2024, January 24). European Defense Agency.

Digitalisation of Defence in NATO and the EU: Making European Defence Fit for the Digital Age. (2023, August 10). IISS.

Healthcare Cloud Computing: Meaning, Advantages, and Implementation Pitfalls. (2023, August 16). IEEE.

How fire departments can extinguish money, space, and data loss with the cloud. (2020, May 11). ZDNET.

Military Cloud Computing Market. (2023, September). MarketsandMarkets.

RISE with SAP Overview. (2024). SAP.

SAP National Security Services Subsidiary. (2024). SAP NS2.

The Future of Cloud Computing in 2027. (2022). Gartner.

Transition to SAP S/4HANA. (2024). SAP.

Why using the cloud is about more than just efficient storage. (2022, September 2). POLICE1.

4 Lessons from Moms in Risk-Resiliency for Supply Chain Professionals

2024-05-10T13:36:56.541000+02:00

This Sunday is Mother’s Day! It is a beautiful day to show our moms, grandmas, or nanas how much we care and appreciate all the things they do for us. They are our first real-time superheroes, setting an amazing example in every aspect of life. So, why not take a cue from moms and incorporate their best practices into our supply chain strategies?

Let's get inspired and see how we can learn from our very first supply chain managers of all time: our moms!

#1 She is the dictionary definition of risk-resiliency.

When I was a kid, each time I tripped and scraped my knee, like a superhero, my mom would come rushing to my rescue with a napkin and band-aid in hand. Or whenever I mentioned I was hungry or thirsty, she'd pull out a magical purse filled with snacks and water. They are constantly one step ahead, knowing our needs and ready for any kind of shenanigans.

Just like how moms, supply chain professionals need to have their special tools in their toolbox to predict, anticipate, and act with agility toward any issues that may arise. If anyone knows how often the ship hits the fan, it's supply chain managers.

One of the most important tools in the supply chain managers’ toolbox is having full visibility to thrive instead of just surviving in the business world. Breaking down silos and sharing real-time information with each stakeholder in the supply chain operations enables businesses to make informed decisions with an agile reflex.

#2 She leverages Momtifical Analysis capabilities.

Let’s be honest, moms never seem to forget a single detail – this is a dad-approved statement by the way - and they are always ready to give us the guidance and support we need to make the optimal decision in seconds.

Much like moms’ ability to make quick decisions, supply chain professionals need the tools to do the same. Incorporating business AI into operations is like the supermom senses of real-time data and insights, enabling supply chain managers to make quick and resolute decisions and guiding businesses through the complexities.

By harnessing the power of data analytics and machine learning algorithms, organizations can pinpoint and address issues in real time, reduce wastage, and improve overall production quality. They prevent potential equipment malfunctions before they occur, schedule maintenance, and safeguard against costly breakdowns and production chokepoints, which enables them to increase efficiency and maximize profitability.

#3 She can effectively alternate sourcing strategies.

Shopping with mom is like embarking on a wild scavenger hunt through the aisles of multiple stores. She knows where to buy the freshest groceries, and always knows when to get them. Moms’ knowledge of suppliers - including the network amongst the local stores and other moms - is so extensive that she is always prepared and alternates sourcing strategies in case their supplier cannot provide what they need.

In today's digital age, an interconnected, transparent, and versatile network is a must for businesses to establish strong connections with their partners and suppliers along the supply chain. Connecting the partners, suppliers, and logistics data in a single centralized environment eliminates the need for individual integrations with each trading partner. This streamlined and centralized network improves risk management and enhances trust, therefore, enhancing customer satisfaction.

#4 She shapes a greener future.

Back in the day, my schoolbag and pockets were like a treasure trove of empty snack packs and wrappers, as my mom taught me to throw away my trash only in the bin. Fast forward to adulthood, I still find myself hoarding trash in my bags, as her voice still rings in my head. The fact is moms are shaping the future by teaching generations to be eco-conscious by instilling habits like repurposing items and cutting down on waste.

Just as mothers are instrumental in making this change, supply chains, as great contributors to waste in the world, are also essential drivers of change and innovation in creating a more sustainable future for our planet.

By implementing sustainable methodologies and tools, the supply chain can become a valuable asset in not only profitable growth but also positive environmental change.

In a world where we are consistently looking for alternative ways to run supply chains more efficiently, why not draw inspiration from our very first supply chain managers we know: our mothers?

To learn more about enabling a risk-resilient and sustainable supply chain, please join us at the upcoming SAP Sapphire & ASUG Annual Conference, from June 3-5, 2024 in Orlando.

Welcome to the Product Inspiration Series for Industries & CX

2024-05-13T15:20:57.917000+02:00

Curious to learn more about SAP Industries & Customer Experience product innovations and seeing them in action? Then what we've prepared is exactly made for you.

According to the motto "Get Ready and Experience Intelligent CX from SAP" we from the SAP product team are happy to invite you to the Industries & CX Product Inspiration Series 2024. Starting in May we are planning to release multiple deep-dive videos made specifically for you, our dear customers, partners, colleagues and all SAP industries & CX enthusiasts out there.

Each product inspiration video covers a specific domain of the Intelligence CX portfolio by highlighting latest innovations and technologies used e.g. SAP Business AI powered scenarios along with Generative AI and SAP Joule.

By definition each video...

does not contain any slides (zero slides rule),
covers specific innovations as part of the Intelligent CX portfolio,
is made from product and/or industry experts for experts,
typically starts with a short Q&A at the beginning (why, what, how),
consists of deep-dive and/or process demos,
wants to inspire you by showcasing real software,
is produced in high quality to offer a jaw-dropping viewing experience,
helps you to understand the Industries & CX product strategy,
and ultimately is made with love and dedication for you.

And here's the list of the first videos which made it through the finish line...

We hope you like it and you're as excited as we are…

Enjoy and have fun!

Technovation Summit 2024: Expand your AI and BTP Horizons

2024-05-13T15:21:27.786000+02:00

This week the SAPinsider Technovation Summit will commence its inaugural event, with the topics of Artificial Intelligence (AI) and SAP Business Technology Platform (BTP) the stars of the show. And following on just a few short months from the last SAPinsider EMEA conference, it will be great to see if the buzz and excitement around these two topics is just as palpable in Barcelona as it was in Copenhagen.

Technovation Summit 2024 is a 1.5-day event designed for anyone interested in AI or SAP BTP and offers an agenda rich in informational sessions and learning opportunities for any technology enthusiast seeking to expand their knowledge and understanding of the development, application and best practices in these two hot topics. And in addition to hearing from a wide range of speakers at the event, there will also be ample opportunity to network and dive into deeper technology discussions with technology experts and industry peers.

Barcelona of course is a wonderful city location for an event like this. After spending a long day inside, absorbing all the sessions that one can fit into a day, building your knowledge and expanding your horizons of the potential that AI and BTP has to offer your business, what better place could there be to then relax and reflect on the day by taking the time to visit the beach, enjoy a city walk, or unwind and eat Tapas in one of the many tavernas on Las Ramblas, while marveling at the diverse and unique architecture.

6 of the Best for Barcelona

The trouble with attending any event, is selecting which sessions to see that will prove to be of most value to you, especially when there are so many opportunities to learn new things. My advice is simple, try and plan as much in advance, and create your personal agenda as early as possible, so that when you get to the event you can spend less time planning and more time networking and seeking answers to the burning questions that are most important to you and your business.

So why don’t I help a little and start you off with some suggestions for your agenda. Let’s simply assume that everyone will plan to attend the day-1 and day-2 keynotes, to be delivered by Iver van de Zand (14 May, 9:30am) and Prof. Marek Kowalkiewicz (15 May, 9:30am) who will share their own insights and experiences of AI, and in the case of Iver BTP too, setting the scene and the tone for each day of the summit. But after the keynotes, what next? Here are my personal 6 picks for Barcelona:

Generating the Future: SAP Business AI and the Generative AI Roadmap, 14 May, 10:45am to 11:30am
AI Ethics – A Primer to Guide your Organization on the Opportunities and Risks, 14 May, 11:45am to 12:30pm
How to Automate Document Streams using SAP BTP and Machine Learning, 14 May, 1:30pm to 2:30pm
Case Study: Moving From On-Premises to The Cloud with SAP Integration Suite, 14 May, 3:00pm to 4:00pm
What's on your Mind? Maximize the Potential of SAP BTP & AI, 14 May, 4:15pm to 5:00pm
What's on your Mind? Unveiling the Magic of Digital Transformation, 15 May, 11:45am to 12:30pm

And, if you don’t mind, I’ll take a liberty and add one more to see. This isn’t strictly a session, but it will cover many topics that are BTP and AI related, and this is delivered in the form of a BTP: Technology News Update, which will take place at the SAP booth during the networking break at 10:15 on 14 May. Please head to the booth to hear from our presenter Carles, and then network with the SAP onsite team to ask them any questions that spring to mind. Don’t be afraid to challenge them – they’ll appreciate you spending the time to talk with them!

Of course, these are just a few suggestions, and there are many more sessions available for you to select from the agenda. Why not take a look at the SAPinsider Technovation Summit website and look at the event sessions list, or even better download the SAPinsider2024 event app to your smart device (available on the App Store and Google Play) and to see a full list of available sessions, and to create your own personal agenda.

Continue Your Learning After the Event

While I’m sure you’ll enjoy your experience and learning opportunities in Barcelona, I expect that you’ll also want to continue your own personal learning journey after the event too. In this case why not explore other learning opportunities from SAP. For example, find out how to build software applications, side-by-side extensions, and integrations to and from cloud applications by exploring SAP’s free learning content on SAP BTP. It is made for both integration designers and extension developers from all levels of expertise and will help you stay up to date with the latest SAP BTP innovations. And check out even more role-based learning resources and opportunities to get certified in one place on SAP Learning site.

For those of you travelling to Barcelona this week, I do hope that you find the SAPinsider Technovation Summit to be an informative and stimulating experience. My best wishes for safe travels, and I hope that you enjoy the event!

Chris Grundy

Product Marketing, SAP BTP

Building and delivering AI solutions for both developers and end-users in SAP S/4HANA Public Edition

2024-05-13T22:45:39.980000+02:00

The first half of 2024 has been an exciting time to be able to share the latest AI innovations coming out of the SAP UX Engineering team. Since the SAP Fiori Innovation Day we hosted in Dublin in February (you can ready Ian Quigley’s recap here), our team has been focused on connecting and collaborating with customers, partners, and colleagues at events around the globe and online to make a number of AI innovations available to you, whether you are developing SAP Fiori apps or consuming them. In this blog, I’ll share some updates on AI solutions for SAP S/4HANA Public Edition; as well as where you can learn more if you are interested in trying them out.

Please note that some of the content in this blog is about unreleased solutions from SAP. SAP reserves the right to change its development priorities at any time, so please do not make any purchase decisions based on what you read here.

Using generative AI to create apps based on business requirement documents and sketches: SAP Fiori tools AI

The 2403 release of SAP Fiori tools introduced the ability to create CAP projects and SAP Fiori elements applications by feeding a business requirement document into Joule, which uses generative AI to understand and build the desired application. This streamlines the application development process, allowing developers to skip the initial configuration of the application and allows them to focus on the additional value-added features that give their end users the tools they need to get their work done. This helps developers be more productive by allowing them to focus on the features that matter.

This initial release is available in SAP Business Application Studio as part of SAP Build Code. In order to use this AI feature, you will need an SAP Build Code license. You can check out our help portal documentation for more information on how to get started.

In some cases, you may not have a fully worked-out business requirement document ready to go but still need to get a demo app running quickly. In that case, we are currently working on another enhancement to this gen AI tool: using Joule to generate an application based on a sketch or mockup. The idea being that you can take a sketch of an application – for example, something you might have from a whiteboarding session – and upload it into Joule to generate the application. SAP Fiori tools AI understands what you intend to build and then generates an application based on an SAP Fiori elements floorplan that best matches your sketch (or high-fidelity mockup). This was born out of collaboration with partners that were looking for a quick way to get started with applications. This will help jump start your SAP Fiori application projects as well, allowing you to develop more apps in less time and freeing you up to focus on the features that make your applications unique.

An enhancement to SAP Fiori tools AI will allow users to create a basic SAP Fiori elements application from a sketch or mockup.

We have had a ton of fun showing a demo of this sketch-based app generation to customers and partners at the above-mentioned SAP Fiori Innovation Day, the brand-new developer community-driven FioriConf, and ASUG Chapter Meetings in the United States. Regardless of whether the audience is online, in Dublin, or in Seattle; we’re very grateful to get the same feedback: “When can I try it?!” SAP Fiori tools app generation from a sketch is still in development, but if you want to see the latest updates, I highly encourage you to check out our team’s session upcoming session at UI5con in St. Leon-Rot on June 5th, 2024. A lab preview of the latest version will be part of the session Adding AI to SAP Fiori elements apps at both design time and runtime.

If you can’t make it to UI5con, stay tuned! We’ll have updates on SAP Fiori tools AI as soon as they are available.

Finding business data in SAP Fiori apps using natural language: Easy Filter

The SAP Fiori user experience is all about building and delivering applications that are role-based, coherent, adaptive, simple, and delightful. This makes the applications easier to learn and use. Still, learning new business processes and filtering applications to get the exact business data you need can take time. In order to further streamline the SAP user experience, simplify onboarding, and enhance how users filter and find information; we are currently working on a solution we call Easy Filter. This planned feature for SAP Fiori apps will allow you to filter the information in the app using natural language. Instead of setting the traditional selection fields, users can simply describe the business information they would like to see in the Easy Filter field.

Easy filter will allow users to filter and find information using natural language.

Additionally, this new AI-assisted way of filtering is planned to allow for more complex, conditional queries – something that is not currently possible with traditional selection fields.

Easy Filter will streamline how you find the information you need, make it easier for users to onboard on new processes, and allow you to make more complex queries if needed, making you more productive overall.

Easy Filter is planned to be part of an upcoming release but if you want to try it out early, be on the look out for an announcement on beta registration coming soon.

Let AI summarize complex business data: Smart Summarization of SAP Fiori apps

SAP Fiori elements object pages display the details of a single business object, for example all of the relevant information for a single sales order for a particular role. Due to the complexity of various business processes, there is the possibility of object pages containing large amounts of information that could make it difficult to find the data you need to move business decisions along. Our Smart Summarization feature, planned to be available in an upcoming release, is an AI-based tool that will summarize the highest priority information for you. This ensures that you have access to all the information you need to drive your work forward and be more productive. If needed, you can also copy the summary for easy sharing in the collaboration tool of your choice.

Smart Summarization will create quick summaries of essential business information on SAP Fiori elements object pages. These summaries can be shared in the collaboration tool of your choice.

If you’re interested in trying this out, stay tuned for a beta registration announcement coming in the near-term future.

Creating insight cards for My Home with Joule

Insight cards for My Home in SAP S/4HANA allow you to display key facts and figures from SAP Fiori elements applications on your My Home page. Traditionally these cards are created from the respective application screens, but we are currently working on a solution to enable you to ask Joule using natural language to create cards with the desired information, without needing to navigate to the app. This will make end-users more productive by ensuring that they have access to all the information they need at a glance, without requiring them to have in-depth technical knowledge typically associated with creating list, table, and analytical cards. This also makes interactions with SAP systems more intuitive for new users, who may know what they need to know but not necessarily know what application they need to find the business data.

Creating Insight cards using natural language will make it easier for end users to get the business data they need without requiring advanced technical knowledge.

This is currently in active development and we can’t give away too much information yet, but keep your eyes open for future updates.

Staying up to date with AI innovations

If you’re excited to learn more about AI innovations coming out of SAP and want to hear them directly from the experts themselves, there are a number of events I can recommend depending on where you are.

For SAP AI enthusiasts in the United States attending SAP Sapphire June 3 -5, 2024; there are a number of great sessions available. My colleague Peter Spielvogel will be personally hosting the session Building better applications for business users with SAP Fiori – this will include AI innovations in SAP Fiori development. He has also put together a blog of further recommendations if you are interested in UX, development, and AI sessions: Sapphire 2024 user experience and application development sessions.

For those of you in Germany, I would highly recommend attending UI5con on June 5, 2024. As mentioned earlier in this blog, my colleagues Katrin Polloczek and Klaus Keller will be hosting the session Adding AI to SAP Fiori elements apps at both design time and runtime. There you will be able to learn how we are working to bring the productivity gains and usability improvements from our AI solutions into SAP Fiori elements.

If these in-person events are not an option for you, continue to watch this space. A number of virtual sessions and informational videos will become available as we prepare to release these solutions. We’re looking forward to hearing what you think!

Unlocking the Potential of Business AI: Engineering Best Practices

2024-05-15T11:19:59.068000+02:00

This blog post is part of a series that dives into various aspects of SAP’s approach to generative AI, and its technical underpinnings.

In the previous blog post of this series, we learnt about benchmarking of AI models. In this blog post, we will discuss some engineering best practices in the field of generative AI. We will understand the concepts with concrete examples.

Read the first blog post of the series.

Introduction

At SAP, we're at the forefront of integrating AI into business applications and platforms. While generative AI holds immense potential to unlock unprecedented value, translating this innovative technology into practical business solutions does not come without its challenges. It demands rigorous adherence to requirements of reliability, transparency, and ethics to achieve business value.

The development of generative AI applications stands at the intersection of AI technology and deep business domain knowledge. Engineering challenges in developing generative AI applications differ from traditional software development due to unique data requirements, the need for specialized evaluation metrics, ethical considerations, and iterative development processes inherent to generative AI. It is a meticulous process that evolves through hypothesizing, experimenting, validating results, and iterating with feedback — each step is a cornerstone in delivering business AI. On the other hand, understanding the business domain is crucial for enhancing efficiency, user experience, and overall value for business users.

This blog post centers around the engineering best practices that underpin the development of business AI use cases at SAP. To explain the approach, we take the integration of generative AI within SAP SuccessFactors’ business applications, with AI-assisted compensation discussions functionality as a specific case in point.

Engineering Best Practices for Generative AI

At SAP, teams are developing a wide range of use cases from question answering, text generation, classification, and summarization to code generation and are exploring the potential of emerging paradigms such as agentic workflows Running mission-critical processes for customers, SAP teams follow a common set of engineering best practices to ensure enterprise qualities. These are discussed below.

1. Foundational pillars for best practices

Figure 1 outlines the core pillars of best practices, the specifics of which will be explored in the next section's use case deep dive. For instance, discussions on data quality will involve counterfactual analysis, while performance testing will be examined through prompt and model benchmarking results. Moreover, issues of security and ethics will be addressed through AI ethics reviews.

Figure 1: Overview of key pillars covered by best practices

Let us understand each of these pillars.

Data quality: At the core of relevant, responsible, and reliable business AI, is the high fidelity of insights data produced by SAP’s business applications. Only with input data of high quality, can we expect a relevant output. SAP's data governance and standards ensure that the data applied is of high quality and semantically rich.

Bias assessment: It is imperative to assess and mitigate any potential biases in the data or model predictions. This is to ensure that the application is also “responsible”, which is one of the three “R”s, as explained in this blog post by our CEO, Christian Klein.

Performance and testing: Rigorously evaluating and testing capabilities guarantees that results are accurate and reliable. At the same time, applications should meet performance criteria in their specific domains, and this should be baked in early in the development process to prevent cost arising from afterthought. Another key consideration is the performance metrics, the selection of which is subject to business objectives and data characteristics.

Monitoring and maintenance: Continuous monitoring leads to identifying and addressing any issues that may arise during usage (such as performance degradation), and proactively and continuously improving capabilities based on feedback, as well as user research. To achieve the best business outcome, we leverage up-to-date technology and tools available.

Security and privacy: Security is not by chance, but rather by design. Following SAP’s strict security standards and data privacy policy, we implement strong authentication, authorization, threat modeling, and regular audits to safeguard business processes and data to keep them protected.

Explainability: Our product is designed around the concept of explainability to foster enhanced trust and greater user engagement. Unlike "black box" producing results without explanation, allowing authorized users to view what contributes to these results is beneficial. For example, this can be implemented through relevant logs or visualizing the raw data in an inference call.

Ethics: Our longstanding commitment to AI ethics policy and guidelines ensures that use cases go through rigorous ethics assessment including commitment to human rights, designing for people, striving for bias-free business, transparency, upholding quality, and safety. This is in direction with our purpose of helping the world run better and improving people’s lives.

2. Following a common generative AI architecture

To enable internal teams to follow best practices efficiently, use cases are developed based on a common architecture described in the first blog post of this series. This architecture provides teams with tools and technology components on SAP BTP including the generative AI hub in SAP AI Core, the SAP HANA Cloud vector engine and SAP Joule. Generative AI hub in SAP AI core provides trusted access to Large Language Models (LLMs), business grounding for LLMs, and LLM exploration as explained in detail in our second blog post of this series.

Use Case Deep-dive: SAP SuccessFactors AI-assisted Compensation

In this section we will deep-dive into SAP SuccessFactors AI-assisted compensation functionality to illustrate how best-practices guide business AI use case development at SAP. This includes a thorough evaluation process that incorporates an AI ethics review.

Figure 2: Focus on three pillars - data quality, bias assessment, and performance/testing

We will prioritize three fundamental categories for our deep dive: Data quality, bias assessment, and performance/testing. Within these categories, we will especially focus on quality and fairness, with key topics illustrated in Figure 2. In the following sections, we will explore these perspectives in detail, including solution accuracy, robustness, cost reduction mechanism, and bias mitigation.

1. Use case background

Discussions about compensation between managers and their direct reports are sensitive and require careful consideration. Each compensation discussion can be different and requires collating many data points such as job profile, compensation history, and organizational pay bands, to understand the employee’s compensation profile. Managers must spend time analyzing various data sources and preparing talking points for each employee. SAP SuccessFactors AI-assisted compensation system facilitates an equitable & efficient approach for managers to get insights into an employee’s compensation. Managers are thus able to have sensitive compensation conversations with easy access to the data insights & talking points personalized for the employee.

LLMs offer enormous potential in this process to be simpler and more efficient. LLMs provide powerful capabilities to automatically extract key points, summarization, and themes from lengthy historical data. They unlock valuable insights on this data, enabling business users, in this case managers, to take the right business decisions efficiently.

However, as mentioned earlier, using LLMs to analyze compensation data presents its challenges. While LLMs are trained on vast amounts of data and can generate human-like text, they struggle with contextual understanding and thus may result in content that is factually incorrect or misleading. Specifically, lacking a comprehensive understanding of the compensation context makes it hard for them to capture pay bands specific to the company, country, or industry. They are not adept at complex mathematical calculations, leading to errors in reporting increments and thus unreliable quantitative metrics. Additionally, SAP SuccessFactors harnesses extensive tabular data. Unlike text and code, which are one-dimensional, tabular data are two-dimensional. LLM’s restricted ability to comprehend two-dimensional tabular data amplifies the overall complexity. Furthermore, achieving impartiality poses a significant challenge, as biases can be intrinsically embedded in model training or user input, presenting a major ethical concern.

Following best practices, we implemented an LLM-based method for employee compensation review by combining tabular data pre-processing and advanced LLM prompt techniques. Table serialization is employed to reduce token count and make data more understandable for LLM. We extensively evaluate accuracy, robustness, and bias to ensure the solution delivered is relevant and responsible. See figure 3 for an example of AI-assisted compensation insights. Also see one minute demo in this video.

Figure 3: Illustration of AI-assisted compensation insights

2. Boosting relevance with advanced prompting and model selection

Accuracy of the AI predictions is key in providing value to our business users. Across use cases, teams are applying an array of prompt engineering and fine-tuning best practices to infuse domain knowledge and customer specific information. The approach is tailored to ensure that each use case meets business requirements and achieves the desired solution quality. For example, as an advanced prompt engineering technique, chain of thought (CoT) prompting facilitates the generation of more controlled, accurate, and relevant outputs through a step-by-step guidance process. Another example is an agentic strategy like ReAct, which empowers LLMs to leverage tools to improve accuracy.

We want to illustrate how best practices for advanced prompting techniques with long and short instruction contexts boost the accuracy of the SAP SuccessFactors AI-assisted compensation.

To create compensation insights, the context that provides instruction and grounding data about the employee is very important. For the compensation analysis processing to perform accurate arithmetic operations, the prompt instructions must be specific and well aligned with the pertinent contextual data.

Figure 4 compares the quantity accuracy of CoT prompts with long and short instruction contexts and a combination of CoT and ReAct prompts. To preserve the prompt-specific response from the LLM, we manually checked the quantity accuracy. The results show that all three prompting techniques achieved high accuracy scores for quantity extraction. The short context CoT prompt achieved the best arithmetic calculation accuracy. This demonstrates that employing advanced prompting techniques effectively yields high accuracies for both number extraction and arithmetic calculation.

Figure 4: Boosting performance by leveraging domain knowledge through advanced prompting techniques

Once the prompt version has been optimized, we choose the most suitable model from a variety of SAP-built and partner models. For example, for our use case we carry out a range of experiments to benchmark models. Continuing with the short context CoT prompt, we conduct additional testing on LLM’s capability to categorize employees by certain categories such as “underpaid”, “overpaid” and “fair paid”, based on their compensation history data (Figure 5). Among five LLMs shown below, GPT-4 significantly outperforms the other models, achieving higher accuracy across all three categories.

A combination of the techniques above supports an LLM-assisted process, well specialized and accurate in examining employee compensation data. This approach may be used in other scenarios too.

Figure 5: Comparison of the ability to classify “underpaid”, “overpaid” and “fair paid” from the employee compensation data

3. Scenario-specific testing for reliable and robust results

The data in customer systems can be diverse, influenced by configuration and employee tenure. It is crucial that the generated insights are pertinent to the given context. This necessitates a regimen of scenario-specific, good coverage testing to ensure prompt is designed for robustness and adaptability.

In the context of the AI-assisted compensation, we follow this best practice and evaluate the LLM’s responses across a range of scenario-specific data inputs, focusing on a variety of scenarios, such as low or high variance in compensation trend, new and long-standing employees, and decreasing compensation ratio as an extreme case. The responses are then subject to human evaluation. A sample of the key findings are shown in Table 1. It can be seen that the prompt performs well across the tested scenarios, achieving high scores overall, although it scores slightly lower in the scenario involving very long compensation history.

Table 1: LLM result quality from various input data scenarios

4. Optimizing and serializing input data for increased relevance and speed

Further to scenario-specific testing, infusing business data into AI use cases is a key component for relevant results. For enterprise use cases this data often comes in tabular form and additional semantic context as provided by SAP’s business applications. This needs to be optimized too.

We begin by ensuring that the context data provided to generate insights is comprehensive to represent the employee’s tenure and compensation progression. Hence optimizing the token footprint of our input is a necessary step to optimize speed. Simultaneously, another goal is to enhance accuracy through structuring the tabular data input in a manner that maximizes the level of comprehension by LLMs.

Table 2 shows a mock data set, representing salary progression of an employee. Like many other applications designed specifically for SAP SuccessFactors, the data for employee information is stored as a tabular format (structured data). However, LLMs are naturally not good at understanding tabular data when incorporated into their prompts. This is because the connection between column headers and corresponding cell values breaks down when read sequentially. For instance, if we pass “2021” from the second row of Table 1 into the LLM, it will not recognize that value “2021” pertains to the column “Year”.

Table 2. An example of the mock tabular data, used for employee compensation review

To enhance the comprehensibility of tabular data for LLMs, we use a text template to serialize it, before passing it to the prompt. The serialization adheres to predefined templates. For example, a simple template can follow the format “The {column_name} is {cell_value}.”. Our tests demonstrate that the proposed serialization method successfully enables the LLM to understand the relations within the tabular data while maintaining a reduced token size leading to faster and more accurate results (approximately 25% fewer tokens compared to the original JSON format).

5. Understanding and mitigating inherent bias with prompt-centric debiasing

LLMs are prone to producing biased completions due to the imbalanced dataset in the training process. Preventing the propagation of bias in generative AI applications presents unique challenges due to their content-generating nature, such as the compensation tool generating talking points. However, we have best practices in place to identify and mitigate bias by applying techniques such as specific prompt engineering or fine-tuning.

To illustrate this in the context of our use case, we examine potential unintended biases by simulating the recommended salary adjustments across different gender groups. This is achieved by alternating between male and female names in the input parameters to represent the respective gender groups, which are then used to invoke LLM API calls. Note that the salary adjustment is not included in the end results presented to users; it is used exclusively for calculating the quantity for internal assessment purposes.

The outcomes of these calls are subsequently analyzed for statistical assessment.

Figure 6: Comparison for scenarios distinguished by gender in input and prompting style

Figure 6 illustrates the evaluation flow for different scenarios based on gender in the input data and various prompting styles. Specifically, we adopt and assess the prompting thinking style via additional instructions to explicitly instruct the model to remain unbiased.

In Figure 7, we compare the distributions of results obtained before and after the use of unbiased style of prompting and gender pronoun removal. It is found that the use of proper prompting leads to a reduction in the bias, where male & female cases receive similar result distributions with tighter bounds. When gender was directly included in the prompt, those identified as non-binary were generally favored by the LLM.

Figure 7: Gender-based group result distributions: before and after (vertical bars represent ranges and dots represent outliers)

The effect of bias reduction is illustrated in Figure 8. We deduce the bias from the discrepancies observed between the two gender groups. More specifically, we calculate the discrepancy between distributions of gender-based results by measuring the difference in their mean values on a standardized scale. In this figure, for instance, employing a basic prompt will lead to a difference of 0.162 between gender groups with GPT-4. However, this difference can be minimized to a much smaller one of 0.049 using the final prompt.

Figure 8: Effect of bias reduction based on discrepancy of gender group mean values

Based on these evaluation of bias mitigation measures, we actively adjustment our approach to reduce bias in production implementation. This includes removing gender information from the prompt context data and adopting unbiased prompting style.

6. Ensuring reliable and responsible AI through ethic review process

In generative AI, ethical considerations are crucial due to its potential usage for completions, summarization, and classification use cases. Ensuring fairness, transparency, and accountability in the generation process is essential to mitigate biases, uphold privacy rights, and promote responsible business AI applications. At SAP, our AI ethics policy mandates that generative AI applications conform to the three fundamental pillars – “Human Agency & Oversight”, “Addressing Bias & Discrimination” and lastly “Transparency & Explainability”.

Figure 9: Pillars of SAP’s AI ethics policy

SAP SuccessFactors has an AI acknowledgment framework that the business users will acknowledge before using/viewing any AI capability. Additionally, the product standards and risk assessment process mandate that all personally identifiable data is handled appropriately and anonymized. Data access controls are applied by existing role-based permissions, and insight data available is restricted to what the user has access to. Based on application type and the data processed, AI use cases are internally categorized by risk level and undergo a review by the SAP AI ethics steering committee to address any potential concerns related to bias and data safety. The AI-assisted compensation discussion use case has had thorough reviews with the SAP ethics steering committee. The review process has resulted in a strengthened warning notice and improvements of both the prompt and insights content to reduce bias.

The improvements involve steering clear of presumed performance, avoiding generic statements, and creating actionable, bulleted points. Following our best practices, users can view all the data sources that are used to generate insights, ensuring explainability and transparency. This process is described in detail as part of SAP AI ethics handbook.

At the same time, we remain compliant with the European Union AI Act on artificial intelligence, which lists manipulation of cognitive behavior, social scoring, biometric identification people, and their categorization based on it, as “unacceptable risks”. Furthermore, there are well defined transparency requirements towards general purpose AI systems, to be considered. Our solutions, including the AI-assisted compensation review, passes these tests, thanks to the above-mentioned stringent AI ethics review.

Conclusion

At SAP, our engineering best practices are tailored to develop ethical, resilient, and scalable generative AI applications. This synergy enables us to unlock the full potential of generative AI within our business applications and platform to enhance efficiency and productivity for our customers.

In this blog post, we illustrated this by exploring the critical intersection of SAP SuccessFactors business domain knowledge and generative AI expertise. We shared examples of engineering best practices applied during the development of AI-assisted compensation discussion scenario. We detailed the best practices by presenting their quantitative effectiveness from various perspectives, including relevance, robustness, reliability, and bias. Additionally, we outlined the AI ethics review that this use case has been subjected to.

Co-authored by Dr. Shu Zhen, Gayatri Gopalakrishnan, Dr. Jan Dumke, and Agarwal, Akhil

Business AI for Aerospace, Defense and Complex Manufacturing

2024-05-16T09:39:46.351000+02:00

How embedded business AI facilitates the next wave of automation and transformation.

In light of the omnipresent debate about the role and potential of Artificial Intelligence (AI) as disruptive force to global business organisations and existing processes, this blog intends to provide an assessment of SAP’s approach to business AI and the application potential for complex manufacturing organisations, such as in the Aerospace and Defense (A&D), or other Engineer-to-Order (ETO) industry sectors.

AI Impact on the A&D Industry

With breakthroughs in traditional and specifically generative AI, A&D / Manufacturing executives have increased their focus on evaluating AI-related initiatives, in disciplines like:

robotic process automation (RPA)
traditionally applied ML e.g., to predict outcomes and probabilities or to discover correlations, anomalies, or clusters, hidden inside massive data sets.
deep learning / Gen-AI applications focusing on natural language processing or image and video object detection and content creation.

There is consensus among industry experts that AI opportunities exist almost everywhere – from core product R&D and air mobility innovations, over optimisation of flight operations and air traffic management to enabling new business models, service, or cybersecurity capabilities.

The focus of this blog will be on opportunities in the core business process framework for commercial and defense aerospace and defense enterprises as well as other complex, ETO centric manufacturing organisations.

Seeking effective ways to respond to current industry challenges and market realities impacting all of A&D and adjacent manufacturing sectors, many companies assess the potential of AI solutions starting with production, supply chain or maintenance operations, hoping to gain much-needed improvements in operational performance or quality metrics. Whether these aim to improve “first time right” scores, order throughput rates or getting more accurate predictions on supplier performance or product margins, many look at AI as a must-have tool for survival in a challenging environment.

The SAP approach to Business AI

SAP’s approach to Business AI, is based on three core principles: It has to be relevant, reliable, and responsible.

SAP’s existing business process platform has been providing best practices and end-to-end solutions for mission-critical industry processes for several decades. By natively embedding AI into this rich foundation of business process and industry data models, we make AI innovations available to enterprises directly where they have the biggest impact, tailored to their specific business context and allowing to re-think existing processes.

Interested in more background? Please start here or take a few minutes to review this blog for a more detailed review of recent examples of selected AI innovations.

Figure 1 - Three sources of value unlocked with SAP Business AI

Business AI applied: A journey towards a future-proof digital enterprise.

With an embedded business AI approach, the AI can work directly on the proven industry data models that SAP has built with thousands of customers over decades and that it can train on the semantics and correlations across your unique custom enterprise data model and landscape – of course considering data protection, ethics, and data privacy standards.

To learn more about SAP’S AI ethics policy, please take a look here.

The enterprise data universe on your SAP platform already collects significant knowledge about actual operational performance values such as supply lead times, non-conformances information, as-built genealogy, or product cost details, that would allow AI services to draw detailed conclusions and arrive at more accurate and relevant predictions on performance, quality, or risk metrics – tailored to each companies’ context.

While we see a broad set of common use cases and value drivers across the industry, we also expect companies to approach AI at their own pace, with their own priorities, and in context of their own realities.

The following structure should therefore only help to exemplify the key patterns and examples that emerged from initial customer and internal conversations.

Figure 2 - Vision: How AI could transform A&D in the future

For most corporations, this journey does not start today or tomorrow, but driven by urgent needs to improve operational efficiencies and master the overarching workforce challenges, companies have already started to look into applying proven technologies that we summarise here under Horizon – 1: Automation and Optimization.

This covers existing AI technology to increase automation of repetitive tasks and processes with robotic process automation, intelligent workflows, and optimize processes with situation handling, or ML processing of unstructured information.

In the same category we also include solutions to provide system users with a more natural user experience, such as chatbots, digital assistants or intelligent content summaries. At this stage, Business AI is applied to augment and improve human decision making by providing intelligent business recommendations with insights.

In initial discussions with some of our A&D customers and partners, we have identified a couple of use case ideas, for example:

Chatbots to assist non-expert users with context-specific system guidance for complex, time-critical processes, e.g., how to assess a production order change scenario or determine program management status information quickly.
Intelligent cross-system workflows and “lights-out” automation of processes like financial closing and billing preparation to avoid manual errors and speed up processes, drive standardisation and scalability.
Automate collection and validation of critical master data to improve quality and accuracy, e.g., supplier lead times, raw material prices, or estimated production scrap rates. Getting these parameters “right”, has massive business impact.

Horizon 2 – Intra-company transformation:

True transformation potential lies in the ability to re-engineer entire E2E processes holistically across silos and teams, instead of focusing only on isolated process steps – and if needed by combining multiple AI technologies.

For example, applying ML to forecast equipment and machine failures as well as ideal maintenance schedules based on historical records, and additional context data can help optimize the maintenance cycles for critical assets and increase their uptime.

But what if companies could automatically use these predictions as input into adjacent enterprise processes, such as production planning (e.g., if my AI can estimate that a production asset is ideally taken out for service or overhaul at a specific time in the near future – so a well-known predictive maintenance use case - what is the impact of this capacity change to the already planned production schedule and what is the optimal solution to adjust this plan – considering customer priorities and shop-floor resource and tool dependencies).

A similar example, that some companies have already started to look into: Use ML to predict short-term risks that deliveries of critical supplier parts to a factory / assembly line will be delayed due to external factors disrupting transportation routes – combined with a recommendation engine that analyses the impact on the production flow and the best options how to re-schedule and move orders in different scenarios.

A Business AI solution that understands all these connection points hidden in the business data model would have significant potential to help companies optimize entire process chains, not just individual sub-processes, for maximum impact.

Horizon 3 – AI on network level cross-company

Of course, the long-term vision of business AI goes far beyond intra-company optimization but could lie in a much more autonomous design and implementation of AI-based processes reaching across company boundaries and connecting information and processes from multiple networks and system layers and hereby moving to a future state in which systems could take more autonomous decisions with high business impact – enabled by intelligent bots that optimize cross-network business flows, e.g. in supply chain planning and fulfillment and also provide more transparency for supply chain planners.

How to apply AI use cases to drive innovation across the A&D Value chain (some ideas)?

SAP and our global partner ecosystem in the A&D and broader Manufacturing space have already started to work on concrete use cases and innovations across the entire range of business processes that impact the main strategic priorities for companies in the A&D space. Some are already available today; other examples are innovation ideas that SAP or our partners might look into in the future.

To stay up to date, I’d recommend to frequently review the latest SAP AI roadmap information (link provided at the end of this blog).

Customer Centricity (all process related to end-customer engagement, proposal management, and business acquisition)

- Generate more profitable proposals and quotes, recommend ideal solution and service proposals, and optimize re-use of historic projects even for complex ETO environments

- A first step in this direction is our SAP Intelligent Product Recommendation offer for CTO processes. Here is an overview: SAP Intelligent Product Recommendation Spotlight Video

Figure 3 - SAP Intelligent Product Recommendation

Agile Innovation and Manufacturing

- AI-supported quality assurance - Improve production efficiency, product quality and non-conformance control with Image / photo-based inspections, ML-powered quality and yield prediction, failure classification, automated root-cause analysis, and recommendations.

To get a first impression how this could look like in our SAP Digital Manufacturing Cloud solution, take a look at the Visual Inspection scenario.

- Asset utilization benefits from maintenance prediction and health monitoring.

- Worker efficiency - Use AR to provide hands-free assistance, digitise knowledge transfer and recommend learnings and training

Responsive Supply Networks

- AI can help making supply chains more resilient by improving demand forecasts and identifying potential supply chain risks and delivery disruptions early on.

- Intelligent optimization of warehouse tasks and space allocation to minimize storage movements and handling cost.

- AI-supported lead time determination - Predict lead time variances more accurately, to improve planning quality and delivery performance

- Forecasting of long-term service part demand.

New Business Models / Aftermarket

- Predict impact of service parts inventory constraints on SLA, use ML to allow planners to run scenarios of potential risks and outcomes to assess impact on performance contracts

- Support authoring of maintenance engineering and planning documents, detect failure patterns in unstructured maintenance records

- Predictive asset maintenance - Leverage IoT and other data sources to proactively identify maintenance issues and use ML for failure modes, anomaly, and root cause detection. Interested how SAP Asset Performance Management works? Take a look here.

Figure 4 - SAP Asset Performance Management

AI - What is next …

With this blog, I have tried to summarise some of the main application and use cases ideas along the typical design-to-operate process flow for manufacturing companies, specifically in the A&D sector.

In one of the next blogs, I’m going to look into some additional aspects in the areas of defining a governance structure for successful AI initiatives and share some updates on innovations.

In the meantime, feel free to reach out to me if you are interested and want more information about use cases and scenarios for Business AI for the A&D and Complex / ETO Industrial Manufacturing Industry sector.

You can start your own research, here are some additional sources:

SAP AI Roadmap with focus on A&D
SAP Store - Partner Solutions for A&D Industry, powered with AI.
Explore SAP for A&D
What is generative AI?

Thank you / Best Regards,
Frank Klipphahn - SAP Industry Expert: Industrial Manufacturing and A&D

Identifying Business Scenarios enhanced by AI

2024-05-16T09:39:59.390000+02:00

Objective: I aim to demystify what represents an AI business scenario by presenting it in layman's terms.

Let's commence with a straightforward task: folding an A4 paper four times and cutting it along the folds. This yields 16 uniformly sized pieces. Reassembling them back into an A4 shape is a simple feat, requiring minimal cognitive effort and time. In this scenario, a basic program or algorithm suffices to guide a computer through the task.

Now, envision a different scenario: tearing the A4 paper randomly into 16 pieces. Here, we encounter a diverse array of shapes and sizes, each fragment boasting its own distinct pattern of torn edges. Reconstructing the A4 sheet from these irregular pieces becomes a formidable challenge, demanding both intelligence and time. In this context, the need for AI becomes evident. Teaching a computer to navigate through this labyrinth of irregular shapes is quintessential for success.

These scenarios parallel the world of data. In the structured scenario, data mimics the uniformity of the paper pieces, easily interpretable and analysable. Conversely, in the unstructured scenario, data assumes a chaotic form, akin to the torn paper pieces. Here, human intervention is necessary to train the computer, enabling it to decipher shapes, measure dimensions, and ultimately, assemble the pieces. This exemplifies the role of AI tools in tackling unstructured data.

In practice, infusing intelligence into computers necessitates vast amounts of data in various formats—text, images, audio, color, and more. Consider the staggering volume of text and images required for a computer to identify a cat or a dog. The magnitude of data required is immense, underscoring the monumental task of imbuing machines with cognitive capabilities.

In systems like SAP, data stored in databases is typically considered structured data. Leveraging this data to extract meaningful insights often requires sophisticated algorithms. Particularly, when algorithms need to analyse data in various forms such as text, images, or natural language, the complexity escalates. In such cases, training the computer to generate insights from this diverse data landscape becomes imperative.

Key Takeaway :

Consequently, scenarios demanding multi-modal data analysis represent prime candidates for Artificial Intelligence applications.

Thank you for your patient reading. Your feedback and insights are invaluable in fostering a collaborative learning environment. Together, we advance our understanding and harness the transformative power of AI.

Develop with Joule in SAP Build Code

2024-05-16T22:12:27.753000+02:00

Authors: @ale_biagi | @YatseaLi

This blog post is part of a webinar series to show you how to explore the Generative AI capabilities of SAP AI Foundation on SAP BTP, along with proof of concepts in the form of use cases. You will have the opportunity to earn a knowledge badge with the title "Generative AI development with SAP BTP" by taking the first three sessions or replays and passing its associated web assessment

Replay: Develop with Joule in SAP Build Code

Here we will explore Generative AI-based code development using Joule in SAP Build Code with a sample use case, following the Clean Core approach and extending SAP S/4HANA Cloud with side-by-side extensibility.

Here you will find the source code of the final solution developed in SAP Build Code with the assistance of Joule: SAP-samples / develop-with-joule-in-sap-build-code

Why Generative AI-based Code Development matters?

Let’s start by reviewing why Generative AI-based Code Development matters nowadays, especially in the context of the SAP ecosystem.

The Developers Dilemma

A recent research from IDC shows that developers spend only 20% of their time doing what they’re supposed to do: develop high quality business applications. The other 80% are spent performing peripheral overhead activities. This has a huge impact on their productivity.

Developers wear many different hats. Instead of spending their time coding developers are having to spend more time performing tests, implementing CI/CD, fine tuning performance and making sure the application is secure. All of this is necessary to create resilient applications, but in the end all developers want to be more productive and produce applications more efficiently.

Developers are more productive when they have the proper tools at their fingertips, when they can easily access data, and when they can reduce or eliminate tedious tasks.

To make a developer more productive, it comes at a cost. Developers need to implement a solution to handle CI/CD, another tool to access API’s, another tool to do transport management and they are always looking at ways to eliminate repetitive tasks. These are ways to increase developer productivity, but it comes at a cost when looking at solutions that come from multiple vendors to support development.

So, what is SAP doing to help with the Total Cost of Development and the Total Cost of Ownership when looking for application and extension development? That's exactly what we will discuss in the upcoming paragraphs.

How does this dilemma affect the SAP ecosystem?

All of you should have already noticed that the core of SAP’s strategy, lies in the Case for Cloud led by the Cloud ERP and its peripheral cloud solutions, powered by the Business Technology Platform as their foundation and driving force.

Such core strategy is executed through two main global programs:

RISE with SAP: focused on the installed base and private cloud;
GROW with SAP: focused on net new names and public cloud

So, what are the biggest roadblocks and challenges when executing this strategy?

For the cases of brown-field conversion, we noticed that technology-driven organizations have historically built on top of standard functionality to extend the capability to meet business needs. However, continuing to maintain decades-old technology now limits benefits and increases the cost of adopting new technologies.

Organizations cannot drive the next level of business transformation while carrying significant technical debt, because they are slower to innovate, more expensive to run and upgrade, and riskier to operate.

And for the cases of green-field implementation, what would be the challenge, then?

Thinking in terms of a cloud mindset, the concept of fit-to-standard should be applied in most of the cases whenever possible, leveraging the high flexibility provided by cloud solutions regarding configurations and personalization. When it’s not possible, a quick implementation for rapid turnaround of digital transformation should rely on the fast development of new loosely coupled solution extensions.

SAP's approach to fast-paced Cloud ERP innovation

And here is where the Clean Core Concept comes into play!

Such concept is essentially based in four main principles:

First, every solution extension should be built as a loosely coupled service instead of a tightly coupled monolithic application
Then, when building such services, as they’re loosely coupled, they’re supposed to extend the transactions from the backend system instead of modifying them in terms of either data and code
To do so, it’s imperative to strictly consume officially released APIs from the backend system, thus ensuring that changes to the core do not affect extensions as those APIs are maintained by SAP and backwards compatibility is guaranteed. This opens the path for continuous innovation through constant upgrades.
And last, but not least, by building extensions in a multi-tenant approach the extended functionality can benefit several customers with one single code-base.

By envisioning this concept as the backbone for continuously evolved cloud software, SAP has provided several tools and technologies in the last couple of years to make it reality for its customers and partners (such as UI5, the Cloud Application Programing Model framework – both NodeJS and Java – coupled with the SAP Cloud SDK – also NodeJS and Java – and the ABAP Cloud with its RESTfull Application Programming model approach).

All of this has been done so that brown-field ERP migrations can clean-up the backend system core and green-field new implementations do not touch the core.

In the context of S/4HANA extensibility, we have basically two scenarios: Core Solution Extensions (also known as On-Stack or In-App Extensions), which run in the same stack of the ERP and the so called Side-by-Side Extensions, running on BTP. I guess you all have already heard about it, right?

In the On-Stack Extensibility we have the Classic Extensibility, which usually modifies transactions’ code and data, and, consequently, is not clean core.

For a clean core approach with start with the Key User Extensibility provided by an extensive set of core personalization functionalities and, on top of those, we add the so called Developer Extensibility which is achieved through the Embedded Steampunk – that can be described as an On-Stack ABAP environment – leveraging ABAP’s RESTfull Application Programming Model (in short RAP).

For the sibe-by-side extensibility powered by SAP BTP (which is clean core by nature), we rely on the broad spectrum of development tools provided by SAP Build and SAP Build Code (which is the focus of this post), and the BTP ABAP Environment.

The dynamics of Generative AI into SAP ecosystem

Now, coming down to the Generative AI topic, here’s how we envision its dynamics into the SAP ecosystem.

The first thing that will change for customers (and SAP) is that we will use GenAI to Build Code. For customers that have legacy applications the typical strategy is to “do nothing”. Do nothing has the advantage of being low effort, but the downside is that it is high risk. Keeping old school applications rife with technical debt and disconnected to other business processes allows digital natives to leapfrog and disrupt your business. The second approach is to use traditional software development approach powered by humans. This is high effort and high risk: it is also really expensive. The third approach is to infuse Generative AI into software development process which we characterize as medium effort and medium risk. As time goes on our intuition this will become table stakes for all organizations. It is really what sets Generative AI apart from traditional ML in terms of disruption and economic value.

The second thing that is going to change is analytics: Generative AI is going to be table stakes for analytical applications. SAP cleverly acquired Ask Data over 2 years ago, and we are close to fully embedding it into SAC and as a pattern within Joule. We will see incredible capabilities emerge within SAC and other embedded analytical capabilities in the near future.

In enterprise applications Generative AI will emerge as a critical capability that powers automation, assistants, and agents. The most obvious example is Joule as an assistant that will power our major LoBs including Success Factors and SAP S/4HANA Cloud (Public Edition and Private Editions).

In this post we will focus on the first and clearly important vertical. For more information about the Generative AI topic in the SAP ecosystem, please refer to this link.

Overview on SAP Build Code and its Generative AI Capabilities

Since it's general availability announcement on March 27th, a lot of good content has been produced about the outstanding capabilities of SAP Build Code. To avoid "reinventing the wheel" we've compiled a short list of selected blog posts describing the many features of SAP Build Code:

We strongly recommend you read through those posts before proceeding with this one. You can also view the session replay for the live SAP Build Code overview.

The Paradigm Shift of Programming with Natural Language

So, there’s no doubt that Generative AI will bring a new paradigm to the context of software development within the SAP ecosystem by introducing Natural Language into the programming process.

To understand this paradigm shift, let’s picture a simple ERP migration to the cloud scenario where we usually have a bunch of tightly-coupled classic extensions which have to be converted into clean core extensions.

In such context we usually have one or more product or business or process owners (in our case here, Mary) reviewing such extensions and making specifications in natural language.

Mary, then, passes those specifications to John (the developer), who refine them by transforming them into prompts, and, in SAP BTP, there’s the SAP Build Code subscription containing the Joule copilot to which John passes the prompts. Based on such prompts Joule is able to generate the application’s data model, service definition, test data, Fiori elements UI and business logic as well as unit test scripts to test the logic.

Finally, using a one-click approach, John can deploy the application to either Cloud Foundry or Kyma.

The Flow of the New Paradigm

Now, let’s take a look into the flow of such process. So, Mary starts by reviewing functionality of legacy on-stack classic extensions in brown-field scenarios or defining new solutions requirements in green-field scenarios. In both cases she prepares the specifications in natural language

Here’s where John come into play, reviewing Mary’s specifications. He, then, performs prompt engineering (now called code generation prompt engineering) to prepare for the solution development.

Next, he enters the prompts in Joule, reviews and accepts (or not) the code, refining the prompts if necessary, does manual adjustments and some additional coding if required (and yes, there’s manual work in the process!), performing unit tests - these three steps are repeated until the desired outcome is achieved - and, finally, john deploys the solution handing it over back to Mary who’s responsible for the final testing and approval.

Development Use Case - Customer Loyalty Management App for Retailers

Well, for this post we designed an inspiring Use Case to showcase the development process with Joule in SAP Build Code in action. This use case is about a customer loyalty program management app for retailers, let’s start by understanding the business scenario:

The business scenario is a customer loyalty program management application for the business partners who make purchases in retailers. It’s a quite simple scenario managed by three personas:

The first one is Mary, an ERP administrator who manages products and business partners in S/4HANA Cloud which provides information to the second persona...
Jane, a loyalty program manager responsible for providing additional loyalty program data and monitoring purchases and redeemed rewards through an S/4 extension.
Finally, there’s Watson, a customer (actually a business partner in S/4) who basically makes purchases of selected S/4 products and redeems the corresponding rewards.

Solution Architecture

Now, let’s see how to design a solution architecture foundation to cover this business scenario:

On one side we have the SAP Business Technology Platform, hosting Cloud Foundry and Kyma run-times and, on the other, there’s the SAP Cloud Solutions with S/4HANA Cloud being one of them.

As previously mentioned, the ERP admin manages products and business partners in S/4HANA Cloud. Our Customer Loyalty solution extension is deployed to SAP BTP (in our case in Cloud Foundry) using SAP HANA Cloud as data persistence and reading Products and Business Partners from S/4HANA Cloud via Destination.

Finally, the Customer Loyalty Manager and the Customer can access the solution through a desktop or mobile device.

The highlighted CAP application is the solution extension that we will develop with SAP Build Code with the assistance of Joule throughout this post.

Fusion Development Approach

This architecture can be alternatively extended to leverage a UI built with SAP Build Apps instead of a standard Fiori UI. In this case, the CAP service is exposed as OData to SAP Build Apps via Destination. This is what we call Fusion Development: a combination of low-code/no-code citizen development with pro-code development.

In this post we will focus on the first approach: Fiori Elements UI.

Demo of the Finished Product

Now, let’s have a look at a live demo of the Customer Loyalty Management application in action:

Build the Use Case with Generative AI-based Code Development

Implementation Steps

Now that we got to know the generative AI-base code development with Joule in SAP Build Code, let’s have a look at the implementation steps that will be examined one by one in detail in the upcoming paragraphs.

We will start with a short demo on how to setup SAP Build Code in your SAP BTP global account
The first block of steps essentially relies on automatic code generation powered by Joule. The steps of this block are:
1. Build and Run the initial base CAP application…
2. Generate NodeJS code for business logic and unit tests…
3. Generate Fiori UI Apps through wizards and enhanced by Joule
The last block is focused on manual coding. Here we will:
1. Manually enhance the app to integrate with S/4HANA Cloud and...
2. Refine the data model and some annotations with manual code.

The above steps are quite well demonstrated in a series of hands-on videos listed below (or you can choose to view the session replay to watch them in sequence):

On-boarding
- Auto Code Generation
  - Build & Run the Initial App
  - Generate Business Logic & Unit Test
    - Business Logic
    - Unit Tests
  - Generate UI Apps
    - Generate Fiori Elements App
    - Generate Free Style UI App
- Manual Coding
  - SAP S/4HANA Cloud Integration
  - Manual Enhancement

Best Practices of Code Development with Joule in SAP Build Code

To get the best from SAP Build Code, here are some best practices that can be considered.

As we have seen in the previous demos, the structured guided development process with proven best practices has been innate in SAP Build Code, which we should follow throughout the whole development lifecycle.

The Storyboard allows you to develop applications using graphical editors and wizards. Use the Storyboard as the entry point to all the artifacts of the project.

In terms of UI, SAP Build Code provides the wizard templates for UI App creation, and the awesome graphical page editor for UI annotation. Use these wizards and graphical page editor instead of Joule for UI.

When using Joule in SAP Build Code, here’s a list of some best practices for prompt engineering:

As a rule of thumb for prompt engineering, the more specific, descriptive, and detailed the prompts are, the better are the results they yield.
Use explicit constraints (e.g. when to use simple associations or compositions in entity relationships).
For Data Modelling, please avoid using technical CDS terms in the Data Model description, such as aspect, enumeration, code list etc. which will be filtered by Joule.
Do not include any detail about the application logic in the Data Model, as it will be ignored by Joule.
In the application logic for actions and unit tests, give detailed information on how data is passed into the request.
For unit tests, provide the appropriate data for positive and negative cases to make sure the tests pass accordingly.
Always review the generated code or data, regenerate if necessary, iterate and fine-tune the prompt as much as needed.
And last, but not least, it doesn’t matter how much you try to be the most precise and perfect in your prompts, there will be always situations when editing the code directly will be quite more quicker and effective.

Still in the prompt engineering topic, when you are not sure how to get started on the solution and need some inspirations, here are some tips:

Get inspiration with the target solution name and its entities in Joule (e.g. “Create a customer loyalty management app with customer, purchase and reward redemption entities”). Joule will automatically generate 5 fields for each entity, so you can take it from here to enhance it further.
Alternatively, ask another LLM chatbot (e.g. Prompt Editor of SAP Generative AI Hub, ChatGPT, etc.) to describe the entities relationship of your solution as an inspiration for data model description(e.g. "Describe the the entities relationship model for customer loyalty management solution"), and edit the generated entities relationship if needed. Then pass it to Joule in SAP Build Code as the prompt for generating the data model.Describe Entity Relationship with Prompt Editor in SAP Generative AI Hub

Findings Summary of CAP Development with Joule in SAP Build Code

Here’s a brief summary of findings gathered during the development process of the customer loyalty extension, with short recommendations. You will notice that only the modification of the business logic and its corresponding unit tests is done with pure manual coding. All the rest can be achieved with full or partial assistance from Joule combined with the productivity tools and some possible manual coding. Our conclusion is that SAP Build Code proves in practice that it’s truly capable of turbocharging software development especially in the context of the SAP ecosystem

Findings Summary

Conclusions and Takeaways

These are the main takeaways we foresee when applying this new development paradigm in the context of the SAP ecosystem, by turbocharging software development leveraging SAP Build Code with the assistance of Joule Copilot:

Speed-up migration of legacy on-stack extensions to the cloud following the Clean Core principles
Safeguard technology investments by avoiding vendor lock-in and reducing TCO
Take advantage of a learning opportunity to quickly adopt industry standard technology and the new natural language programming paradigm
Accelerate time-to-market with quick prototyping and monetization of solution extensions
And last, but not least, prepare for fast-paced future innovations peculiar to cloud software either in the backend system and in the extensions themselves

Frequent Asked Questions:

During our webinar sessions, there are quite a number of questions have been raised. Here summarize the the most frequent asked questions and answers.

Q1: Can we use Joule to refactor an existing CAP project?

Answer: Not as of 14 May 2024. However, the new feature of Refactoring existing CAP code using generative AI is under development and scheduled for Q2 of 2024.
It allows developers using Joule to generate SAP Cloud Application Programming Model (CAP) data models, application logic, and unit tests to:

Add or remove an entity
Add, modify, or remove the properties of entities
Create or remove associations between entities
Get more support on a service projection definition

Please find more detail here.

Q2: Can the classic CAP NodeJS application(not generated by Joule) leverage the productivity tools such as Story Board, Page Editor etc.?

Answer: As of 14 May 2024, the productivity tools is now only available in SAP Build Code. However, it will be also available in SAP Business Application Studio for classic CAP NodeJS Application development, which is planned for Q2 2024. Please check here for more detail.

Q3: Can I use Joule in SAP Build Code for CAP Java Application development?

Answer: As of 14 May 2024, only CAP NodeJS Application development is supported with Joule in SAP Build Code. However, CAP Java Application development is planned in Q3 2024. Please check here for more detail.

Q4: How can I jump start with SAP Build Code?

Answer: Please follow this developer tutorial to have a test drive with SAP Build Code.

Q5: What license do I need to use SAP Build Code? Do I need SAP Generative AI Hub in my SAP BTP Global Account for it?
Answer: You will just need the license and entitlement of SAP Build Code in your SAP BTP account to use it. No extra license required.

SAP Build Code is available on Trial and the Free-tier plan of SAP BTP for free evaluation, and commercially available through SAP BTPEA and Pay-As-You-Go for production. For partners, it is also available in TDD license.

Q6: What are the differences between SAP Build Code and SAP Business Application Studio?

Answer: SAP Build Code is built on top of SAP Business Application Studio with generative AI capabilities for code generation, guided development and end-to-end unified development experience of SAP solution and extension. It offers unparalleled efficiency and effectiveness in application development.

Q7: What is the future of SAP Business Application Studio? We have seen the evolution of SAP Web IDE, then SAP Business Application Studio, Now SAP Build Code.

Answer: SAP Business Application Studio remain as a separated product for development of classic CAP application, Fiori application, mobile application development etc. It will be also evolved and improved overtime. For example, The productivity tools such as Story Board, New Fiori Template Wizard and Page Editor will be also available in Business Application Studio to improve the developer efficiency and experience. However, the generative-AI capabilities are exclusively available in SAP Build Code. Please check its roadmap for more detail.

Q8: When should I choose SAP Build Code? And When should I use ABAP side-by-side or On-stack extensibility for Clean Core development?

Answer: It is not a simple answer, which depends on the use case and technical capability of the team. Here you have use case pattern of SAP S/4HANA Cloud extension in high-level.

On-Stack Extensibility:

Adapt SAP Standard applications(UI, Custom Field, Custom Data Model) through public extension point
Full-stack application or new integration in embedded steampunk with public local API

Side-by-Side Extensibility:

Full-stack application: single tenant, multi-tenant SaaS, hub scenario.
Mobile applications
Process Automation among multiple systems

Please to go through Extension Architecture Guide for more details.

Q9: Will be similar generative-AI capability available for ABAP?
Answer: Yes. Similar generative-AI capability is planned for ABAP Cloud. Please stay tuned.

Q10: Is it Clean Core only applicable with side-by-side extensibility? How about On-Stack extensibility?Answer: Not, Clean Core can be through both On-Stack extensibility and Side-by-Side extensibility.

Q11: Is there any plan to make extension development easier for SAP S/4HANA Cloud with SAP Build Code?
Answer: There are some features planned in SAP Build Code about closer integration with ABAP, such as:

Additional Material

In this final section, we have compiled additional materials you can check, in order to deepen your knowledge on this topic:

Generative AI at SAP

SAP Build Code

Additional Materials of this session

Use Cases of Generative AI in SAP Cloud ALM

2024-05-17T07:17:43.942000+02:00

Introduction:

Generative AI can significantly enhance SAP Cloud ALM (Application Lifecycle Management) by automating, optimizing, and enriching various aspects of application lifecycle processes. Here are some key use cases:

1. Automated Documentation and Reporting

Generative AI can automatically generate detailed documentation and reports based on system activities, logs, and user inputs. This includes:
- Creating system configuration documents.
- Generating compliance reports.
- Summarizing project progress and milestones.

2. Incident Management and Resolution

By leveraging AI, SAP Cloud ALM can:
- Automatically categorize and prioritize incidents based on historical data and predefined criteria.
- Generate suggested solutions and troubleshooting steps for known issues.
- Create incident resolution summaries and documentation.

3. Predictive Maintenance and Monitoring

Generative AI can predict potential system failures and maintenance needs by:
- Analyzing system performance data and identifying patterns indicative of future issues.
- Generating maintenance schedules and tasks proactively.
- Providing alerts and recommendations for preemptive actions.

4. Change Impact Analysis

AI can analyze proposed changes to the system and predict their impact, such as:
- Generating impact assessment reports for software updates or configuration changes.
- Suggesting risk mitigation strategies.
- Creating detailed test plans based on potential impact areas.

5. Test Case Generation and Optimization

Generative AI can enhance the testing process by:
- Automatically generating test cases based on user stories, requirements, and past defects.
- Optimizing existing test cases by identifying redundancies and gaps.
- Generating test data that mimic real-world scenarios for comprehensive testing.

6. Process Optimization

AI can identify inefficiencies and suggest optimizations by:
- Analyzing process logs and user interactions.
- Generating recommendations for process improvements.
- Creating simulation models to predict the impact of proposed changes.

7. User Assistance and Training

Generative AI can support users by:
- Generating personalized training materials and user guides based on role-specific activities.
- Creating chatbot interactions that provide real-time assistance and guidance.
- Summarizing complex processes into easy-to-understand steps and visuals.

8. Resource Planning and Management

Generative AI can enhance resource management by:
- Predicting resource needs based on project timelines and historical data.
- Generating resource allocation plans to optimize project delivery.
- Providing suggestions for resource reallocation in response to changing project requirements.

9. Custom Code Analysis and Recommendations

For custom developments within SAP environments, AI can:
- Analyze custom code for potential improvements and optimizations.
- Generate recommendations for code refactoring to enhance performance and maintainability.
- Create detailed reports on code quality and adherence to best practices.

10. Enhanced Collaboration

AI can facilitate better collaboration among team members by:
- Generating summaries of project discussions and meetings.
- Creating collaborative workspaces with AI-generated agendas and action items.
- Analyzing team performance and suggesting ways to improve collaboration.

Conclusion:

By integrating generative AI into SAP Cloud ALM, organizations can achieve greater efficiency, accuracy, and agility in managing their application lifecycles, ultimately leading to improved system performance and business outcomes.

Expert Systems in AI: Bridging Human Expertise and Machine Intelligence

2024-05-18T19:46:44.716000+02:00

Artificial Intelligence (AI) is a broad field focused on creating intelligent machines capable of emulating human intelligence. AI expert systems specifically aim to replicate human expertise and decision-making processes within specific domains. These systems leverage knowledge bases, rule sets and inference mechanisms to provide recommendations or make decisions, imitating the problem-solving capabilities of human experts.

Need for an AI Expert System:

AI expert systems offer consistent decision-making and problem-solving processes, ensuring a high level of expertise is consistently applied across various scenarios eliminating bias. This reliability enhances the quality of outcomes.
These systems excel at handling complex problems involving vast amounts of data. They can analyze intricate situations and derive rule-based insights that may be challenging for humans to process manually.
Expert systems automate routine tasks, decision-making processes and problem-solving activities, leading to reduced errors, time savings and increased productivity within organizations.
They also play a crucial role in retaining and preserving valuable knowledge and expertise within an organization, even as experts retire or leave the organization.

Inference Engine - crucial component of AI expert system. An inference engine is the component that processes logical rules and knowledge stored in the knowledge base to make inferences to derive conclusions.
Knowledge Base - core component of an expert system, containing information, facts, rules and heuristics related to the domain of expertise.
Knowledge Acquisition Module - responsible for acquiring knowledge from domain experts and translating it into a format that the expert system can understand.
Explanation Facility - expert systems include an explanation facility that can explain the reasoning process behind the system's recommendations or decisions. This transparency helps users understand why a particular solution or suggestion was provided.

How is an AI expert system different from ML Model?

The key difference between a machine learning model and an expert system is the expert systems rely on explicit domain knowledge and rules provided by experts, while machine learning models learn patterns and relationships directly from data through training. Machine learning models are completely data driven, whereas an expert system is rules, facts, objectives and domain-specific knowledge provided by human experts.

Expert systems are often used when human expertise is critical and rules are well-understood, while machine learning excels in tasks where large amounts of data can provide insights and predictions.

How to build an expert system?

Define the problem statement the expert system will address. Identify the specific tasks, decisions, or problems that the system will help with.
Next is the Knowledge Acquisition from domain experts. This can involve document reviews, expert interviews and extracting rules, facts and heuristics that experts use to make decisions in the domain.
Choose an appropriate knowledge representation method which could be rule-based or case-based (storing and retrieving past cases) or a combination of these approaches.
Develop the inference engine which is responsible for applying the knowledge rules to the input data or user queries to derive conclusions or make recommendations.
Last step is to design a user interface through which users can interact with the expert system.

Can we fine-tune a Large-Language Model to an expert system?

While it's theoretically possible to convert a large-language model into an expert system, the process is complex and the resulting system may not fully capture the richness and nuances of human-provided expert knowledge. It's more practical to use LLMs for tasks where their strengths are like natural language understanding and content generation

Large language models learn implicit knowledge from vast amounts of data and then derive patterns and relationships. This may not capture human-provided rules in an expert system. Converting the learned representations of a large language model to use structured knowledge representation such as rules, facts and ontologies can be crucial and may require significant effort.
Large language models are general-purpose models trained on diverse data, whereas expert systems focus on domain-specific data.
Bigger large language models like GPT-3 have complex internal structures that are not easily interpretable or explainable. Whereas expert systems are designed with transparency and interpretability as key features

Applications of AI Expert Systems:

Medical Diagnosis - AI Expert Systems are used extensively in healthcare for diagnosing diseases, interpreting medical images like X-rays and MRIs to provide decision support to healthcare professionals.
Financial Services - In the financial sector expert systems assist in risk assessment, fraud detection, investment advisory, credit scoring and portfolio management based on market trends and economic indicators.
Manufacturing and Quality Control - In manufacturing and quality control expert systems help optimize the manufacturing processes, monitor quality control, schedule maintenance tasks and improve overall operational efficiency
Education and Training - Expert systems are used in e-learning platforms to create intelligent tutoring systems and personalized educational content tailored to learning styles.
Customer Support and Chatbots - Chatbots powered by expert systems provide personalized customer support, answer queries, troubleshoot technical issues, recommend products or services and handle routine tasks through natural language processing (NLP) and machine learning.

Tools and Platforms:

Java Expert System (Jess)
CLIPS (C Language Integrated Production System)
PyKnow
Prolog

Conclusion:

Overall, AI expert systems leverage domain knowledge, logical reasoning and inference capabilities to emulate human expertise and provide valuable insights and solutions in complex problem-solving scenarios. They are a powerful tool for augmenting human decision-making, improving efficiency and addressing challenges in diverse fields.

Regards,

ArunKumar Balakrishnan