AI systems

  • Release version: Zurich
  • Updated March 12, 2026
  • 2 minutes to read
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    Summary of AI systems

    An AI system in ServiceNow is an AI-powered solution developed, deployed, and managed under a formal governance framework to ensure responsible, compliant, and risk-aware operation throughout its life cycle. These systems support organizational business activities by enabling automation, enhancing data-driven decisions, and improving process efficiency. AI systems typically include components such as machine learning models, natural language processing engines, or computer vision tools, supported by datasets, algorithms, and computing infrastructure.

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    Each AI system undergoes a structured evaluation to assess risks related to functionality, security, and societal impact, ensuring compliance with regulations, industry standards, and internal policies. Governance frameworks enforce ethical principles like fairness, accountability, and transparency through controls and oversight, with regular monitoring to mitigate unintended consequences.

    Key Features

    • AI System Record and Aggregated Risk Score: The AI system record in ServiceNow provides an aggregated risk score that consolidates individual risk assessments (e.g., bias, drift, security) from various AI assets using the Risk assessment for AI inventory methodology.
    • Risk Score Visibility: The aggregated risk score is available under the Details tab of the AI system record but requires the Advanced Risk application and enabling the "Migrate to Advanced Risk Assessments" property.
    • Related AI Assets: The system lists associated AI models and datasets, providing a comprehensive view of components contributing to the AI system’s operation and risk profile.
    • Request Related Tasks: Users can request AI use cases, models, or datasets linked to the AI system, streamlining AI asset management and governance.

    Key Outcomes

    • Enables organizations to manage AI systems with structured governance ensuring responsible and compliant AI use.
    • Provides consolidated risk visibility at departmental and enterprise levels, facilitating oversight of AI risks across multiple models, teams, and business units.
    • Supports proactive mitigation of risks such as bias and security vulnerabilities by delivering explainable, fair, and trustworthy AI outcomes.
    • Enhances collaboration through integrated tracking of AI assets and related requests, improving management efficiency within ServiceNow’s AI governance framework.

    An AI system is an AI-powered solution that is developed, deployed, and managed under a formal governance framework. This framework ensures that the system operates in a responsible, compliant, and risk-aware manner throughout its life cycle.

    An AI system functions within an organization’s digital or operational environment to support business activities. It enables automation, enhances data-driven decision-making, and improves overall process efficiency. The system includes components such as machine learning models, natural language processing engines, or computer vision tools.

    These components are often supported by datasets, algorithms, and computing infrastructure. Together, they enable the system to analyze data, recognize patterns, and generate outcomes with minimal human intervention. Each AI system is subject to a structured evaluation process. This process assesses potential risks related to functionality, security, and societal impact. It also verifies compliance with applicable regulations, industry standards, and internal governance policies.

    Governance frameworks are applied to manage the AI system throughout its life cycle. They ensure that the system operates securely and delivers predictable, explainable, and trustworthy results. Ethical principles such as fairness, accountability, and transparency are enforced through defined controls and oversight mechanisms. Regular monitoring supports responsible AI use and reduces the risk of unintended consequences.

    The following image shows the overview page of an AI system.
    Figure 1. AI system overview page
    AI system overview page
    An AI system 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.

    The following image shows the aggregated risk score section:
    Figure 2. Aggregated risk score
    Details page of an AI system showing the aggregated risk score

    Related AI assets

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

    • AI models: The AI models within this AI system.
    • Datasets: The datasets used within this AI system.