Regulatory Compliance Automation in MCP Deployments
Agents need runtime governance because MCP shifts compliance decisions from code to behavior.
Senior Correspondent, AI Governance
Priya Subramaniam spent eight years covering data protection and enterprise risk for a consortium of European regulatory publications before pivoting to AI policy in 2019. She focuses on the intersection of compliance frameworks and autonomous systems, with particular attention to how organizations translate regulatory mandates into operational controls.
12 stories
Agents need runtime governance because MCP shifts compliance decisions from code to behavior.
EU regulators are enforcing AI governance rules that NIS2 never explicitly mention.
Build HIPAA controls into the MCP server itself, not as an afterthought downstream.
Autonomous agents break SOC 2's core assumptions about control and accountability.
Thousands of exposed AI servers put enterprises at risk of major GDPR violations.
Enterprises must map agentic AI to existing Act rules without a special regulatory category.
Attackers exploit LLMs' inability to distinguish instructions from data in tool descriptions.
Three fields in your tool schema determine whether AI agents can run wild or stay locked down.
Most companies have AI governance policies on paper but fail to actually operate them day to day.
Governance frameworks that let agentic AI respond faster without losing audit trails.
How to build identity, access control, and observability before agents go live.
Most enterprises can't see the AI tools their workers use, let alone control them.