What data governance policies should be in place before deploying an AI agent?

At minimum: a data classification scheme (what's sensitive vs. public), access control policies (which agents access which data), data processing agreements with LLM providers, retention and deletion policies, audit logging for all agent data access, and an incident response plan for data breaches involving agent systems.

Data Governance

Written by Max Zeshut

Founder at Agentmelt

The policies, processes, and standards that control how data is collected, stored, accessed, used, and disposed of within an organization. For AI agents, data governance determines what data the agent can access (least-privilege access controls), how it processes sensitive information (encryption, anonymization), where data is sent (which LLM providers, what jurisdictions), and how long it's retained. Poor data governance in agent deployments creates compliance risk (GDPR, HIPAA violations), security vulnerabilities (over-privileged agents), and trust erosion (customers learning their data was sent to third-party AI providers without consent).

Frequently asked questions

What data governance policies should be in place before deploying an AI agent?: At minimum: a data classification scheme (what's sensitive vs. public), access control policies (which agents access which data), data processing agreements with LLM providers, retention and deletion policies, audit logging for all agent data access, and an incident response plan for data breaches involving agent systems.

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