--- title: Map a field to an expected response description: Map a field of a use case to an expected response. AI uses the field mapping to identify a non-standard clause in a contract document. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/employee-service-management/contract-management-pro/cmpro-na-exp-res-mapping.html release: australia product: Contract Management Pro classification: contract-management-pro topic_type: task last_updated: "2026-03-12" reading_time_minutes: 3 keywords: [Contract analysis, Contract analysis expected response mapping, Expected response for contract analysis fields, Expected response mapping, Clause mapping, Now Assist in contract management pro, ServiceNow Otto for Contract Management Pro, AI for contract management pro] breadcrumb: [Configure contract analysis, Configure AI capabilities, Configure, Contract Management Pro, Legal and Contract Operations, Employee Service Management] --- # Map a field to an expected response Map a field of a use case to an expected response. AI uses the field mapping to identify a non-standard clause in a contract document. ## Before you begin Role required: sn\_cm\_gen\_ai.ai\_contract\_config, sn\_cm\_core.contract\_config ## Procedure 1. Navigate to **All** > **Admin Center** > **AI Admin Hub** to access the **AI Skills** tab of the AI Admin Hub console. 2. Navigate to **Employee** > **CM Pro**. 3. Select **Activate skill** on the skill you want to activate. \[Omitted image "cmpro-NA-skills.png"\] Alt text: AI skills available for Contract Management Pro. 4. In the General details page, view the skill details and select **Save and continue**. 5. In the Use case page, select **Save and continue**. For more information on creating a use case, see [Create use cases for contract analysis](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/employee-service-management/contract-management-pro/cmpro-na-usecase-ca.md). 6. In the Clause mappings page, select **Save and continue**. For more information on mapping a field group to a clause, see [Map a field group to a clause](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/employee-service-management/contract-management-pro/cmpro-na-map-fieldgrp-clause.md). 7. In the Expected response mappings page, select **New response**. 8. On the form, fill in the fields.
| Field | Description |
|---|---|
| Use case | Use case that the field is associated with.**Note:** Only active use cases for contract analysis are displayed in the list. |
| Request table | Table that the contract analysis is executed from.**Note:** - The Contract Request table \[sn\_cm\_core\_contract\_request\] is selected by default to centralize the configuration on a single table and improve reusability across product lines. You can choose a different table for the mapping. - For standalone requests the configurations should be done on the Contract Request table \[sn\_cm\_core\_contract\_request\]. |
| Field | Field \(question prompt\) that is mapped to the expected response.**Note:** Only active fields are displayed in the list. |
| Expected response | Expected response:- Yes: When AI returns the same response as expected, the system considers the field as standard. - No: When AI returns a response that differs from the expected answer, the system considers the field as non-standard. All such fields within a field group are categorized as non-standard and are displayed in transaction results with AI-generated comments in both the workspace and Word Add-in. |
| Applies when | Conditional fields that are based on an expected response.**Note:** If this condition fails, the expected answer isn't considered. For more information on using the condition builder, see [Create a condition statement using the condition builder](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/platform-user-interface/create-cond-state-using-cond-build.md). |
| Order | Order in which the expected response is evaluated if a field has been mapped to multiple responses.AI evaluates the expected response from the lowest ordered number to the highest ordered number. AI stops evaluating when the expected response is satisfied. |