> For the complete documentation index, see [llms.txt](https://docs.sprinto.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sprinto.com/data-library/ai-systems/dashboard-actions/monitor-ai-system-violations.md). # Monitor AI System Violations The Violations section in Sprinto helps organisations monitor AI-related policy breaches, sensitive data exposure risks, and governance concerns across AI systems. Violations monitoring helps organisations: * Detect AI-related policy violations * Review sensitive data exposure * Identify risky AI usage patterns * Monitor organisational AI activity * Investigate user activity * Maintain governance oversight Sprinto centralises AI-related governance signals within the Violations tab. *** ## Navigate to Violations To access AI system violations: 1. Log in to the Sprinto dashboard. 2. Navigate to **Data Library**. 3. Select **AI Systems**. 4. Open the **Violations** tab.
The Violations tab displays AI-related governance and compliance violations detected across AI systems. *** ## Violations Inventory The Violations table provides visibility into detected governance issues. The inventory may include: * Rules violated * Violated by * AI system * Violated on * Severity This helps organisations centrally review governance and compliance concerns. *** ## Review Violated Rules Sprinto surfaces the specific governance or compliance rule associated with each violation. Examples may include: * Detect PII in user input and output * Detect PHI in user input and output * Detect legal or contractual information in user input and output These detections help organisations identify unsafe or non-compliant AI usage. *** ## Review Associated Users Each violation is mapped to the associated user activity. The Violated by column helps organisations: * Identify users involved in the activity * Investigate governance concerns * Review risky usage patterns * Track repeated policy violations This improves accountability and governance visibility. *** ## Review Associated AI Systems Violations are also mapped to the related AI systems. This helps organisations: * Identify risky AI systems * Review governance posture * Prioritise governance reviews * Assess AI-related operational risks The AI system association helps connect violations with governance workflows such as: * Risk assessments * Due diligence reviews * Findings and remediation * Governance monitoring *** ## Severity Levels Sprinto classifies violations using severity levels. Depending on your configuration, severity levels may include: * Low * Medium * High * Critical Severity classifications help organisations prioritise investigations and remediation activities. *** ## Search and Filter Violations The Violations tab supports filtering and search workflows. You can: * Search for violations * Filter by AI systems * Review violation history * Monitor governance trends This helps organisations efficiently investigate governance concerns. *** ## Relationship Between Violations and Shadow AI Violations may also be surfaced during Shadow AI discovery workflows. This helps organisations: * Identify unmanaged AI systems * Detect risky AI usage patterns * Investigate unsanctioned AI activity * Bring discovered systems into governance workflows Violations monitoring and Shadow AI governance work together to improve organisational oversight. *** ## Governance Investigations Organisations can use the Violations workflow to investigate: * Sensitive data exposure * Risky AI prompts * Unapproved AI usage * Compliance gaps * Unsafe operational behaviour Violation investigations can additionally lead to: * Findings creation * Remediation tasks * Risk reassessments * Governance reviews *** ## Governance Monitoring Workflows The Violations section supports continuous AI governance monitoring. Sprinto helps organisations: * Review organisational AI activity * Detect governance gaps * Monitor policy compliance * Track high-risk AI activity * Maintain governance visibility across teams This helps organisations strengthen AI governance posture over time. *** ## AI Governance Best Practices When reviewing AI system violations: * Investigate high-severity violations promptly * Review repeated user violations carefully * Reassess risky AI systems periodically * Review sensitive data exposure patterns * Bring unmanaged AI systems into governance workflows * Document remediation activities where required * Maintain audit-ready governance records *** ## Related Information * [AI Systems Overview](/data-library/ai-systems.md) * [How AI Systems Work](/data-library/ai-systems/how-ai-systems-work.md) * [Discover and Govern Shadow AI](/data-library/ai-systems/dashboard-actions/discover-and-govern-shadow-ai.md) * [Assess AI System Risk](/data-library/ai-systems/dashboard-actions/assess-ai-system-risk.md) * [Manage Findings and Tasks](/data-library/ai-systems/dashboard-actions/manage-findings-and-tasks.md) --- # Agent Instructions This documentation is published with GitBook. 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