AI Governance & Risk Management
How do I discover unapproved AI tools employees are using and build an AI inventory?
Shadow AI — employees and teams using AI tools nobody approved — is now a legal exposure, not just an IT annoyance: an AI inventory is the starting requirement of essentially every framework, from the EU AI Act to NIST AI RMF. How to find it: 1. Traffic discovery: AI-traffic security tools identify which AI services your organization actually talks to — WitnessAI monitors employee AI usage, Aurascape decodes AI app protocols natively, Cisco AI Defense includes AI asset discovery. 2. Expense and SSO sweep: cross-check SaaS spend and identity-provider logs against known AI vendors; the gap between the two lists is your shadow inventory. 3. Register everything: move findings into a governed inventory — Credo AI and Trustible are built for exactly this registry function. 4. Set the policy before enforcing it: an amnesty period beats a ban; bans create better-hidden shadow AI. Then keep the inventory alive: re-scan monthly, because the tool list your employees use changes faster than your policy does.
cited_tools
Tools that solve this
WitnessAI
Enterprise
Enterprise AI observability and policy guardrails for safe employee and app AI usage.
Trustible
Enterprise
AI governance platform for inventory, risk assessment, policy, and regulatory compliance workflows.
Credo AI
Enterprise
AI governance platform for model registries, risk assessments, and EU AI Act conformity.
Cisco AI Defense
Enterprise
Cisco's end-to-end AI security: asset discovery, model testing, and runtime guardrails covering prompts, responses, and MCP traffic.
Aurascape
Enterprise
AI-traffic security that decodes AI app protocols natively, enforcing policy at the tool-call level with cross-action data lineage.
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