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Governing Agentic AI at Scale on Google Cloud with JFrog

Coding agents are moving fast, but ungoverned AI assets are creating a security blind spot most teams don’t see until it’s too late.

Every new AI asset your developers pull – model, MCP, skill, or plugin – needs review. Without automated policy enforcement, that review becomes a bottleneck that stalls delivery or gets bypassed entirely.

JFrog and Google Cloud dive in on how teams in regulated and high-scale environments are closing the governance gap, enabling developer velocity without sacrificing security or control.

What you’ll learn:

  • Why governance is the real bottleneck: how the explosion of third-party AI assets creates supply chain risk, shadow AI, and over-privileged agent access.
  • How JFrog AI Catalog works: automated policy enforcement, tool-level permissions, and self-serve access that let developers move fast within trusted guardrails.
  • Why enterprise-grade AI matters:how to ensure your teams build on secure foundations as agents start talking to agents in production.
  • Governing agents in regulated industries: what secure deployment looks like in financial services, healthcare, and other high-stakes environments.
  • How JFrog and Gemini Enterprise work together: runtime governance meets supply chain governance across the full agent lifecycle.

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