--- title: Data readiness for implementing AI on the ServiceNow AI Platform description: High-quality data that is complete, accurate, and contextually relevant is the foundation for delivering precise, meaningful, and trustworthy AI responses. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/intelligent-experiences/sn-ai-impl-data-readiness.html release: australia topic_type: concept last_updated: "2026-09-10" reading_time_minutes: 3 keywords: [Now Assist, agentic AI, AI readiness] breadcrumb: [ServiceNow AI implementation, Enable AI experiences] --- # Data readiness for implementing AI on the ServiceNow AI Platform High-quality data that is complete, accurate, and contextually relevant is the foundation for delivering precise, meaningful, and trustworthy AI responses. ## AI requires high-quality data To unlock the full potential of AI on your instance, the quality of your data is paramount. For AI to deliver accurate, context-aware, and actionable outputs, it must be trained and operate on high-quality data that is complete, consistent, and structured. When your data is well-prepared, AI can process user queries with greater accuracy, enabling faster resolutions and more effective self-service experiences. Whether it's summarizing complex incidents, generating resolution notes, or creating knowledge articles, AI requires detailed records that reflect the full lifecycle of a task. Short or incomplete cases often lack the depth needed for meaningful AI processing, which can result in vague or unhelpful responses. The importance of data readiness extends beyond technical accuracy—it directly impacts user trust and adoption. Clean, ready data also accelerates implementation. It minimizes the need for rework, reduces deployment friction, and helps AI features like summarization, recommendations, and workflow guidance operate reliably from the start. This leads to more consistent outcomes, helping teams focus on strategic tasks. Moreover, high-quality data fosters trust in AI outputs. When users consistently receive reliable and context-aware responses, their confidence in the system grows—driving adoption. Ultimately, data quality supports user satisfaction and AI performance. Follow these tips to assess your organization's data readiness: - Audit task records for completeness and clarity, and ensure resolution fields are consistently filled out with clear summaries. - Avoid using vague or generic language in task descriptions and updates. - Maintain a clean and structured knowledge base and ensure that knowledge articles are linked to resolved cases. For details, see [Knowledge Base readiness for AI on the ServiceNow AI Platform](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/sn-ai-impl-kb-readiness.md). - Audit Service Catalog items. For details, see [Service Catalog readiness for AI on the ServiceNow AI Platform](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/sn-ai-impl-srvc-catalog.md). - Use the AI Readiness Evaluation app to assess catalog, case, and knowledge data. - Use the AI Data Kit to curate and cleanse data sources. - Align stakeholders \(data owners, product managers, and engineers\) around shared standards for AI-ready data. For details, see [AI governance on the ServiceNow AI Platform](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/sn-ai-impl-governance.md). For more information, see [Data Readiness Checklist](https://mynow.servicenow.com/now/best-practices/assets/now-assist-data-readiness-checklist). ## AI Readiness Evaluation app Data readiness assessments can be time-consuming and manual, especially when evaluating whether catalog items are conversational or if knowledge articles are embedded in inaccessible formats like PDFs. The AI Readiness Evaluation app helps automate this process by analyzing service catalog entries, cases, and incidents, and then providing actionable recommendations to prepare data for AI use. It also enables you to assess whether updates, installations, or customizations of your instance could affect implementation. The assessments provide direct hyperlinks to improve any issues found. For more information, see [AI Readiness Evaluation](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/now-assist-readiness-evaluation/now-assist-readiness-evaluation-landing-page.md). Install AI Readiness Evaluation by requesting it from the ServiceNow Store. Visit the [ServiceNow Store](https://store.servicenow.com/sn_appstore_store.do#!/store/home) to view all the available apps, and for information about submitting requests to the store. For cumulative release notes information for all released apps, see the [ServiceNow Store version history release notes](https://www.servicenow.com/docs/r/store-release-notes/sn-store-release-notes.html). ## AI Data Kit If the base system generative AI skills don't fit your needs, use the AI Data Kit to curate, cleanse, and manage data for AI evaluations. You can create custom datasets and data collections that can be used in AI Skill Kit for evaluation. For more information, see [AI Data Kit](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/now-assist-data-kit/now-assist-data-kit-landing.md).