Topic starter
02/08/2026 12:09 pm
TL;DR: Enterprise AI crossed from copilots into production infrastructure in 2025, with agents, MCP, and governance moving into core systems as firms operationalised execution, control, and accountability, according to Akto. The central issue is no longer whether AI is used, but whether organisations can see, scope, and govern what these systems can do before they act.
Editorial analysis by NHI Mgmt Group, based on content published by Akto: “2025 AI Yearbook: The Year AI Became Enterprise Infrastructure”.
Key questions
Q: What breaks when AI agents can chain tools through MCP without tight policy controls?
A: What breaks is the separation between request, authorisation, and execution.
Q: Why do autonomous AI workflows increase the need for stronger identity and permission controls?
A: Autonomous workflows can execute decisions faster than humans can review them, which magnifies the impact of excessive access or weak governance.
Q: How should security teams govern AI-enabled workflows that can act on their own?
A: Treat them as identity-governed execution paths, not just software features.
Practitioner guidance
- Audit AI tool reachability Map every agent, MCP endpoint, and delegated tool path to the systems and data they can reach, then classify each path by business criticality and revocation owner.
- Constrain runtime authorisation Use task-scoped permissions that expire with the workflow so the agent cannot retain broader access than the specific action requires.
- Require pre-action policy gates Move approval, policy enforcement, and exception handling to the point where the agent requests execution, not after a downstream log review.
Bottom line: AI's shift into enterprise infrastructure changes the primary security problem from model usage to governed execution and reachability.
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02/08/2026 1:13 pm
MCP is no longer a transport detail; it is an access plane. Once agents can connect to external tools through shared protocol interfaces, the security question shifts from model capability to reachable systems. That means discovery, approval, and revocation matter more than interface novelty. Practitioners should treat MCP inventory and trust scope as core identity governance, not optional architecture metadata.
A few things that frame the scale:
- 24,008 unique secrets were exposed in MCP configuration files in 2025 alone, the protocol's first year of widespread adoption, according to the State of Secrets Sprawl 2026.
A question worth separating out:
Q: How can organisations prove their AI controls are actually working?
A: Look for evidence that policy decisions are logged, sensitive prompts are being redacted or blocked when required, and approved AI interactions are traceable by identity and business context. Effective programmes produce audit-ready records, not just policy text. If the control cannot explain what happened in a session, it is not operational enough.
👉 Read our full editorial: AI became enterprise infrastructure in 2025, and control now matters