--- sourceDocument: Yokohama Governance, Risk, and Compliance sourceDocumentLink: https://www.servicenow.com/docs/r/yokohama/governance-risk-compliance Release : - yokohama ft:locale : - en-US ft:publication_title : - Yokohama Governance, Risk, and Compliance ft:clusterId : - grc bundleId : - grc workflow : - Technology --- # AI-generated recommendations for similar control objective # AI-generated recommendations for similar control objective {#ariaid-title1} * Release version: Yokohama * * Updated April 27, 2025 * * ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of AI-generated recommendations for similar control objective The AI-generated recommendations framework in the Yokohama release (updated April 27, 2025) enhances compliance management by providing actionable, AI-driven suggestions for similar control objectives directly within the ServiceNow user interface. This framework helps compliance managers and analysts identify, deduplicate, and rationalize similar control objectives, streamlining the compliance library and improving decision-making. Show full answer Show less ## Key Features * **Configurable recommendations and actions:** Allows definition and customization of recommendations and follow-up actions for various record types, integrated within workflows for seamless action. * **Intelligent recommendations:** Utilizes advanced AI technologies, such as generative AI and Predictive Intelligence, to deliver relevant suggestions that improve over time through machine learning and predictive scoring. * **Scalable design:** Supports multiple recommendations per record, customizable layouts for administrators, and adaptability across diverse record types and recommendation methods. * **Adoption enablement:** Designed for rapid integration with upstream products, featuring an intuitive interface that empowers users with clear, actionable insights. * **Control objective deduplication and rationalization:** Automates identification of redundant control objectives to maintain an efficient compliance library. ## Key Outcomes * Improved contextual visibility into similar control objectives for better decision-making. * A flexible, scalable framework that adapts to various organizational processes and record types. * Accelerated adoption for customers leveraging AI/ML recommendations in compliance management. * Enhanced user productivity with built-in actionable recommendations and clear next steps. ## Practical Considerations for Customers * Access to generate recommendations requires specific roles: `snrecotemplate.rationalizationprocesswriter` and `sngrcsharedgenai.compliancegenaiuser`, which must be manually assigned. * Enabling recommendations involves configuring Now Assist for Integrated Risk Management (IRM) and activating the rationalization skill. * The Recommendations page organizes information into sections such as Control Objectives, Description, Response Actions, and Evaluation of Affected Associations, providing comprehensive details for each recommendation. * User interactions with recommendations are tracked in a feedback side-panel to monitor accepted, skipped, or dismissed suggestions. ## Next Steps To utilize this framework effectively, customers should: * Assign the necessary roles to compliance users to enable recommendation generation. * Configure Now Assist for IRM and activate the rationalization skill for control objectives. * Review and act on recommendations via the Recommendations page to maintain an optimized compliance library. * Refer to related documentation on configuring ServiceNow Otto and activating rationalization skills for detailed setup guidance. The recommendations framework is designed to deliver actionable, AI-driven recommendations for similar control objectives directly within the user interface. It provides rich contextual information about similar control objectives, empowering users to make well-informed decisions and take follow-up actions seamlessly. The Control objective deduplication and rationalization feature is designed to help compliance managers and analysts streamline their compliance processes by identifying, deduplicating, and rationalizing similar control objectives within their compliance library. This feature leverages AI to automate the identification of redundant control objectives, helping to make it easier to maintain a clean and efficient compliance library. ## Highlights of the recommendation framework {#ai-generated-recommendations-for-similar-control-objective__section_tdz_vsk_dfc} Configurable recommendations and actions : * Enable you to define and configure recommendations for various record types. * Enable setup of follow-up actions, so you can act on recommendations directly within the workflow. {#ai-generated-recommendations-for-similar-control-objective__ul_e4c_1zc_52c} Intelligent recommendations : * Leverage advanced AI capabilities, including generative AI and Predictive Intelligence, to display relevant recommendations. * Continuously improve insights and recommendations by incorporating machine learning models and predictive scoring. {#ai-generated-recommendations-for-similar-control-objective__ul_mlm_xyc_52c} Scalable design : * Support the display of multiple recommendations for a single record type. * Provide flexibility for administrators to customize the layout and structure of the recommendation panel according to business needs. * Adapt to a variety of record types and recommendation techniques, confirming consistency and scalability across use cases. {#ai-generated-recommendations-for-similar-control-objective__ul_nlm_xyc_52c} Adoption enablement : * Designed for rapid integration and adoption across upstream products. * Offer a user-friendly, intuitive interface that empowers decision-makers with clear, actionable insights. {#ai-generated-recommendations-for-similar-control-objective__ul_plm_xyc_52c} ## Key benefits {#ai-generated-recommendations-for-similar-control-objective__section_i2x_vvk_dfc} * Contextual visibility into recommendations for better decision-making. * A scalable, configurable framework adaptable to various use cases and record types. * Faster adoption for products looking to leverage AI/ML-based recommendations. * Customizable workflows and logic to meet specific organizational processes. * Improved user productivity with actionable recommendations and clear next steps built directly into the interface. {#ai-generated-recommendations-for-similar-control-objective__ul_hny_wvk_dfc} Note: Only users with sn_reco_template.rationalization_process_writer and sn_grc_shared_genai.compliance_gen_ai_user can see the option to generate recommendations for similar control objective. This role must be manually assigned to a compliance user. To generate recommendations for a control objective you must configure Now Assist for integrated risk management and activate the rationalization skill, refer to [Configure ServiceNow Otto for Integrated Risk Management (IRM)](https://www.servicenow.com/docs/rEpDYhPc3zsHoi4n1m3fXw "If you have the admin role, you can configure ServiceNow Otto for IRM so that your agents can use the generative AI skills in the IRM workspace.") and [Activate the rationalization skill for control objective](https://www.servicenow.com/docs/8HBW5ichzm1109kFPtHF1w "Activate and then configure the recommendation for a similar control objective skill under rationalization from Now Assist to generate recommendation which are similar to the selected control objective.") for more information. ## Viewing recommendations {#ai-generated-recommendations-for-similar-control-objective__section_ehf_yxk_dfc} After generating recommendations for similar control objectives, the Recommendations page displays the following sections: * Recommendation * Control objectives * Description * Response actions * Evaluate affected associations {#ai-generated-recommendations-for-similar-control-objective__ul_vfw_2yk_dfc} The following tables provide more information on the sections and the related lists that are associated with the recommendations.{#ai-generated-recommendations-for-similar-control-objective__table_ybw_jyk_dfc__entry__2} | Field | Description | |-|-| | Control objectives | Details of the control objective. For example, the name of the control objective and parent. | | Last refreshed | Date and time the recommendations were last generated or refreshed. You can select the refresh icon ![Refresh icon.]() to view the latest recommendations. | [Table 1. Recommendations] {#ai-generated-recommendations-for-similar-control-objective__table_ybw_jyk_dfc} Note: For more information about control objectives, see [Structural overview of Policy and Compliance Management](https://www.servicenow.com/docs/puEABXwwoBi5byX0aHsgPw "The structural overview of Policy and Compliance Management enables you to understand how the different modules that make up the Policy and Compliance Management application of ServiceNow integrate and interact with one another."). {#ai-generated-recommendations-for-similar-control-objective__table_lxg_ryk_dfc__entry__2} | Field | Description | |-|-| | Description | Description and a summary of the control objective. | | Supplemental guidance | Additional guidance on how to address the control objective. | [Table 2. Details of the control objective] {#ai-generated-recommendations-for-similar-control-objective__table_lxg_ryk_dfc}{#ai-generated-recommendations-for-similar-control-objective__table_cq5_syk_dfc__entry__2} | Field | Description | |-|-| | Impacted Items (Controls, Policy exceptions, Issues, and more) | Related lists containing items directly affected by the consolidation of new control objectives. | | Associated Items (Entities, Entity type, policies, citations, control objectives and more | Related lists containing all associations from accepted control objectives in a consolidated view. | [Table 3. Evaluate affected associations] {#ai-generated-recommendations-for-similar-control-objective__table_cq5_syk_dfc} Feedback trail side-panel: The feedback side-panel displays the history of user interactions with recommended items. This can include what the user accepted, what they skipped or ignored, and what they dismissed. For more information on generating recommendations, see [Use Recommendation of similar control objectives skill to generate suggestions](https://www.servicenow.com/docs/tl7ax7hJ95QJjddd_ooThQ "Generate recommendations by identifying, deduplicating, and rationalizing similar control objectives within the compliance library. This enables identification of redundant control objectives, making it easier to maintain a clean and efficient compliance library."). **Related tasks** * [Activate the rationalization skill for control objective](https://www.servicenow.com/docs/8HBW5ichzm1109kFPtHF1w "Activate and then configure the recommendation for a similar control objective skill under rationalization from Now Assist to generate recommendation which are similar to the selected control objective.")