Topic starter
02/08/2026 12:05 pm
TL;DR: AI security summits are shifting toward agents, MCP workflows, shadow AI, threat detection, and governance, Akto reports in its roundup of 2026 events. Identity, authorisation, and accountability now have to track delegated access and revocation as much as model quality.
Editorial analysis by NHI Mgmt Group, based on content published by Akto: “AI Security Summit 2026: Global CISO Conference”.
Key questions
Q: Why do AI agents and MCP-connected workflows create new data exposure risks?
A: AI agents and MCP-connected workflows expand access beyond human users into systems that can retrieve, transform, and move sensitive data automatically.
Q: What are the warning signs that AI governance is becoming a control gap?
A: The warning signs are fragmented inventories, undocumented OAuth grants, unclear ownership of AI tools, and inconsistent evidence for what each system can access.
Q: How should security teams govern AI agents that can choose tools at runtime?
A: Security teams should govern runtime agent choice as an access event, not as a simple application action.
Practitioner guidance
- Define an AI agent inventory Track each agent, its owner, its tool connections, and the business purpose it is allowed to support.
- Bind MCP access to task scope Limit each tool connection to the smallest required dataset, action set, and session duration.
- Treat agent offboarding as a control Remove credentials, API access, tokens, and workflow hooks when an agent is retired or replaced.
Bottom line: AI security summits in 2026 are reflecting a shift from general model risk to the governance of agents, tools, and delegated access.
Glossary terms: Agentic AI, MCP Workflow, Shadow AI, Agent Identity
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This topic was modified 2 days ago by NHI Mgmt Group
02/08/2026 1:10 pm
AI security summits now function as governance signal events. The conference agenda is shifting toward AI agents, MCP, shadow AI, and threat detection because those are the places where control failures are becoming visible. That means the market is moving from AI experimentation to AI supervision, and practitioners should read the agenda as a map of emerging control debt.
A few things that frame the scale:
- Only 13% of organisations feel extremely prepared for the reality of agentic AI despite the majority racing toward autonomous adoption, according to the 2026 Infrastructure Identity Survey.
- Gartner predicts that by the end of 2026, 40% of enterprise apps will feature task-specific AI agents.
A question worth separating out:
Q: Should organisations treat AI agents like human users in IAM?
A: No. Human IAM assumes a person logs in, works within a session, and can be reviewed later as a stable identity holder. Agents can act at machine speed, across multiple systems, and with changing runtime context, so they need identity governance built around execution and delegation rather than human authentication patterns.
👉 Read our full editorial: AI security summits in 2026 reflect rising agent governance risk