
AI agents are now standard in enterprise workflows but most organizations have no idea they've created a governance time bomb. When agents connect to Salesforce, Snowflake, Tableau, and a dozen other systems through separate MCPs, the result is a fragmented audit trail with no single record of who accessed what data, under whose authorization, or how an answer was generated. Under GDPR, HIPAA, SOX, and the EU AI Act, that's big regulatory exposure. Join Shawhin Mosadeghzad and Terrence Sheflin as they examine why multi-MCP architectures create compliance gaps that traditional data governance tools weren't built to address, and why the fix has to happen at the access point. We'll discuss how a single governed semantic layer acts as the sole MCP for AI data access, enforcing row- and column-level security, logging every query with full user attribution and deterministic lineage, and satisfying the individual attribution requirements regulators are actively closing in on without sacrificing architectural control or LLM flexibility.
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