Source: https://sprinto-test.docs-staging.pageloop.ai/data-library/ai-systems/dashboard-actions/assess-ai-system-risk # Assess AI System Risk The AI Systems module in Sprinto includes AI-specific risk assessment workflows that help organisations evaluate the governance, operational, and compliance risks associated with AI systems. Risk assessments help organisations: - Evaluate AI-related risk exposure - Classify AI systems by risk level - Maintain governance records - Support AI compliance workflows - Prioritise reviews and remediation - Maintain periodic risk reviews Sprinto supports configurable AI risk scoring workflows aligned with evolving AI governance requirements. --- ## Navigate to the Risk Score Tab To access AI system risk scoring: 1. Log in to the Sprinto dashboard. 2. Navigate to **Data Library**. 3. Select **AI Systems**. ![](/assets/8074cf53a54d-screenshot-2026-05-12-at-12.22.21.png) 3. Open an AI system from the **Added AI Systems** tab. 4. Select the **Risk score** tab. ![](/assets/a0fe2124dc39-screenshot-2026-05-12-at-14.28.01.png) The Risk score tab displays all configured AI risk factors and associated scoring values. --- ## How AI Risk Scoring Works Sprinto evaluates AI system risk using configurable risk factors. Each risk factor contains: - Multiple scoring options - Configurable score values - Risk contribution logic As users select values for risk factors, Sprinto automatically: - Calculates cumulative risk scores - Assigns risk levels - Updates governance posture across the AI inventory --- ## AI Risk Factors Risk factors help organisations evaluate the impact and governance posture of AI systems. Depending on your configuration, risk factors may evaluate: - Operational scale - Deployment exposure - Data sensitivity - Decision reversibility - Affected user groups - AI output usage - Business criticality - Regulatory impact - Safety-related usage Risk scoring workflows can be customised from the Configuration tab. --- ## Add Risk Factor Values To assess AI system risk: 1. Open the AI system. 2. Navigate to the **Risk score** tab. 3. Click **Add value** beside a risk factor. ![](/assets/2e4cec638160-screenshot-2026-05-12-at-14.29.16.png) This opens the risk scoring drawer. --- ## Score AI Risk Factors Inside the risk scoring drawer: 1. Expand each risk factor section. 2. Review the available scoring values. 3. Select the appropriate value. 4. Repeat the process for all mandatory risk factors. ![](/assets/cbd1c17c33a4-screenshot-2026-05-12-at-14.30.39.png) Sprinto displays scoring values as selectable options for each factor. --- ## Mandatory Risk Factors Some risk factors may be marked as mandatory. The **Save changes** button remains disabled until: - All mandatory risk factors are scored - Required selections are completed This helps organisations maintain consistent risk assessments. --- ## Save AI Risk Scores After completing the assessment: 1. Click **Save changes**. ![](/assets/1a98f56585b8-screenshot-2026-05-12-at-14.31.37.png) Sprinto: - Saves the selected values - Calculates cumulative risk scores - Updates the AI system risk posture - Displays updated scores in the Risk score tab --- ## Review Risk Scores After saving, the Risk score tab displays: - Risk factor values - Assigned scores - Calculated risk levels This helps organisations review how individual risk factors contribute to the overall AI risk posture. --- ## Edit Risk Scores To update existing risk scores: 1. Navigate to the **Risk score** tab. 2. Click the edit icon beside the risk factor value. ![](/assets/ecb2dcc1c456-screenshot-2026-05-12-at-14.32.20.png) 3. Update the required scoring values. 4. Click **Save changes**. ![](/assets/c5eea85c2dad-screenshot-2026-05-12-at-14.33.22.png) Sprinto recalculates the AI system risk score automatically. --- ## AI Risk Levels Sprinto supports configurable AI risk levels. Depending on your configuration, risk levels may include: - No risk - Low risk - Medium risk - High risk - Critical risk Risk levels are automatically assigned based on configured score thresholds. --- ## Risk Scoring Configuration AI risk scoring workflows are configurable from the Configuration tab. Administrators can customise: - Risk factors - Risk factor values - Score thresholds - Mandatory scoring requirements - Risk level ranges This helps organisations align AI governance workflows with internal risk policies. --- ## Example AI Risk Dimensions AI risk assessments may include factors such as: ### Data Privacy Evaluates how AI systems handle sensitive or personal data. Examples include: - PII handling - PHI exposure - Data retention practices - Training data usage --- ### Operational Scale Evaluates the deployment scale of the AI system. Examples include: - Internal team usage - Organisation-wide deployment - Public-facing deployment - Population-scale usage --- ### Business Criticality Evaluates the operational importance of the AI system. Examples include: - Customer-facing workflows - Revenue-impacting systems - Internal automation tools - Low-impact support systems --- ### Decision Impact Evaluates how AI outputs influence users or business decisions. Examples include: - Human-reviewed recommendations - Automated decisions - Access control decisions - Safety-related outcomes --- ## AI Governance Best Practices When assessing AI system risk: - Review risk assessments periodically - Include compliance and security stakeholders - Evaluate sensitive data exposure carefully - Document business-critical AI usage - Reassess risk after major system changes - Align scoring criteria with governance requirements - Maintain evidence for audit reviews --- ## Relationship Between Risk and Due Diligence Risk scoring helps organisations determine: - Whether additional due diligence is required - Which AI systems require governance reviews - Which systems need periodic reassessment - Which systems may require remediation activities Higher-risk AI systems may require: - Additional document collection - Security questionnaires - Governance reviews - Management approvals --- ## Monitoring AI Risk Workflows Sprinto supports governance monitoring workflows related to AI risk. Examples include: - AI system risk should be scored - Periodic risk assessment reviews - Management review workflows - Risk reassessment monitoring These workflows help organisations maintain ongoing AI governance oversight. --- ## Related Information - [AI Systems Overview](/data-library/ai-systems) - [How AI Systems Work](/data-library/ai-systems/how-ai-systems-work) - [Add and Manage AI Systems](/data-library/ai-systems/dashboard-actions/add-and-manage-ai-systems) - [Perform AI System Due Diligence](/data-library/ai-systems/dashboard-actions/perform-ai-system-due-diligence) - [Configure AI Systems](/data-library/ai-systems/dashboard-actions/configure-ai-systems)