This issue highlights the challenge of aligning an LLM’s “latent ontology” with a company’s “structural ontology” to avoid agent errors, and warns that unmanaged shadow AI magnifies existing governance and security gaps. It also covers Zscaler’s new zero-trust platform for AI agents, Salesforce’s acquisition of m3ter for usage-based billing, and Ivanti’s patch for Sentry vulnerabilities.

• The hard part of enterprise AI isn't building an ontology—it's detecting where the LLM's latent concept-space drifts from the company's defined one, since that drift is what causes agents to pull wrong data and err.
• Shadow AI tools are proliferating unmanaged through SaaS, identity platforms, and API keys, amplifying governance and security blind spots IT already failed to close with cloud and access control.
• Zscaler launched a zero-trust security stack specifically for AI agents (AI Broker, Endpoint AI Security, AI Access Graph, plus expanded AI Protect with red-teaming) to monitor and restrict agent-to-agent and machine-to-cloud traffic.
• Salesforce acquired m3ter to build usage-based billing directly into Agentforce, letting it meter AI compute/API consumption natively instead of enterprises stitching together third-party billing tools.