AI-generated recommendations for similar control objective

  • Release version: Yokohama
  • Updated April 27, 2025
  • 2 minutes to read
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    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 recommendations framework provides AI-driven suggestions for similar control objectives within the user interface, allowing compliance managers and analysts to make informed decisions and execute follow-up actions efficiently. It includes a deduplication feature to streamline compliance processes by automating the identification and rationalization of redundant control objectives in the compliance library.

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    Key Features

    • Configurable Recommendations and Actions: Users can define recommendations for various record types and set up follow-up actions within workflows.
    • Intelligent Recommendations: Utilizes generative AI and Predictive Intelligence for relevant insights, enhancing accuracy through machine learning and predictive scoring.
    • Scalable Design: Supports multiple recommendations for a single record type and allows administrators to customize the recommendation panel's layout based on business needs.
    • Adoption Enablement: Features a user-friendly interface for quick integration, providing actionable insights that facilitate decision-making.

    Key Outcomes

    • Enhanced visibility into recommendations for improved decision-making.
    • A flexible, scalable framework suitable for various use cases.
    • Accelerated adoption of AI/ML recommendations across products.
    • Customizable workflows tailored to specific organizational processes.
    • Increased user productivity through actionable insights integrated directly into the interface.

    Note: Only users with specific roles can generate recommendations. Ensure that Now Assist for integrated risk management is configured and that the rationalization skill is activated to utilize this feature effectively. After recommendations are generated, users can view detailed sections including control objectives, descriptions, and response actions, along with a feedback trail side-panel to track user interactions with recommended items.

    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

    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.
    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.
    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.
    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.

    Key benefits

    • 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.
    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 Now Assist for Integrated Risk Management (IRM) and Activate the rationalization skill for control objective for more information.

    Viewing recommendations

    After generating recommendations for similar control objectives, the Recommendations page displays the following sections:
    • Recommendation
    • Control objectives
    • Description
    • Response actions
    • Evaluate affected associations
    The following tables provide more information on the sections and the related lists that are associated with the recommendations.
    Table 1. Recommendations
    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.
    Note:
    For more information about control objectives, see Structural overview of Policy and Compliance Management.
    Table 2. Details of the control objective
    Field Description
    Description Description and a summary of the control objective.
    Supplemental guidance Additional guidance on how to address the control objective.
    Table 3. Evaluate affected associations
    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.

    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.