Datasets

  • Release version: Yokohama
  • Updated July 31, 2025
  • 2 minutes to read
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    Summary of Datasets

    A dataset in ServiceNow is a curated, structured collection of data designed to support the development, deployment, and monitoring of AI systems while ensuring compliance with organizational policies, regulations, and ethical standards. It plays a critical role in AI governance by capturing essential information such as risk assessments, compliance status, ownership, audit trails, and performance metrics. This enables effective oversight, accountability, and informed decision-making across the organization.

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    The quality and relevance of datasets directly affect AI model performance, fairness, and accuracy. Datasets must be evaluated for completeness, accuracy, and alignment with their intended use cases. Identifying and mitigating bias within datasets is crucial to avoid unfair or inaccurate AI predictions. Maintaining data lineage enhances traceability, transparency, and accountability in dataset usage and management. Compliance with data protection regulations and organizational data policies is mandatory, along with regular dataset reviews and updates to address evolving standards and business needs.

    Key Features

    • Aggregated Risk Score: Each AI dataset record provides an aggregated risk score that consolidates individual risks (such as bias, drift, and security) from related entities using the Risk assessment for AI inventory methodology. This score is visible in the AI system record’s Details tab, offering a holistic view of AI risks at departmental or enterprise levels.
    • Advanced Risk Assessment Integration: The aggregated risk score feature requires enabling the "Migrate to Advanced Risk Assessments" property and the installation of the Advanced Risk application. This integration facilitates a consolidated risk profile across multiple AI models, teams, and business units, improving organizational risk visibility and management.
    • Related AI Assets: The dataset record links to related AI systems and AI models that utilize the dataset, enabling traceability and a clear understanding of dataset dependencies.

    Practical Benefits for ServiceNow Customers

    • Ensures AI datasets are managed with governance, compliance, and ethical considerations in mind, reducing operational and regulatory risks.
    • Provides a consolidated risk view to proactively identify and address AI risks such as bias, helping maintain trust in AI outcomes.
    • Supports transparency and accountability through detailed lineage tracking and audit trails for datasets tied to AI assets.
    • Enables continuous improvement of datasets through regular reviews, ensuring AI models remain accurate and relevant to business needs.

    A dataset is a curated collection of structured data used to develop, deploy, and monitor AI systems in line with organizational policies, regulations, and ethical standards.

    The AI dataset supports governance objectives by capturing key information about AI models, including risk assessments, compliance status, ownership, audit trails, and performance metrics. It also enables effective oversight, accountability, and decision-making within the organization. The quality and composition of a dataset directly impact the performance, fairness, and accuracy of the AI model. Well-curated datasets help verify models learn meaningful patterns and generate reliable outputs in real-world scenarios.

    Each dataset should be evaluated for completeness, accuracy, and relevance to the intended use case. Bias in datasets can lead to unfair or inaccurate model predictions and should be identified and mitigated. Tracking data lineage helps verify traceability, transparency, and accountability in how datasets are used and maintained.

    Datasets must comply with data protection regulations, including privacy laws and organizational data handling policies. Regular reviews and updates help maintain dataset quality and reflect evolving data standards or business needs.

    The following image shows the overview page of datasets.
    Figure 1. Datasets overview page
    Datasets overview page
    An AI dataset record provides an aggregated risk score. The individual risk scores for entities, that have Risk assessment for AI inventory as the Risk Assessment Methodology (RAM) roll-up and form an aggregated risk score. You can see the aggregated risk score under the Details tab of the AI system record in the Aggregated risk score section. For more information about how risk score is rolled up, see Risk score rollup in Advanced Risk Assessment.
    Important:
    To see the aggregated risk score, you must enable the Migrate to Advanced Risk Assessments (sn_risk_advanced.migrate_to_advanced_risk) under All > Advanced Risk > Properties.
    Note:
    You can see this section only if the Advanced Risk application is installed.

    Aggregated risk score consolidates individual risks such as bias, drift, and security, to inform departmental or enterprise-level AI risk profiles, enabling higher-level visibility and oversight. For example, several customer-facing AI models exhibiting signs of bias can lead to organizational risks. Aggregated risk score enables the AI Risk and Compliance team to obtain a consolidated view of AI risks across multiple models, teams, and business units, moving beyond fragmented risk assessments.

    Related AI assets

    The Related AI assets section lists the following for an AI dataset:

    • AI systems: The AI systems that use this AI dataset.
    • AI models: The AI models that use this AI dataset.