Topic starter
11/11/2026 6:00 pm
TL;DR: 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems, according to IndyKite research in the 2026 Infrastructure Identity Survey. IAM decisions now have to account for workflow context, not just the actor that started the task.
Editorial analysis by NHI Mgmt Group, based on content published by IndyKite: “Agentic AI needs a new control model”.
Key questions
Q: Why does delegation context matter in agentic authorization?
A: Delegation context matters because an agent’s authority must be tied to the human owner, task, timeframe, tool scope, and data scope that justified the grant.
Q: What is the difference between authentication and authorization in agentic systems?
A: Authentication proves who or what is acting.
Q: How should teams govern agents that use both model calls and tool calls?
A: Treat the full workflow as one identity problem, not two separate control problems.
Practitioner guidance
- Define workflow-level authorization boundaries Map the full agent path from user intent through tool calls, APIs and downstream actions, then decide where approval, policy checks and traceability must occur.
- Carry delegation context across every hop Preserve who initiated the task, what authority was delegated, and what policy context accompanied each decision so downstream actions stay attributable.
- Bind consent and provenance to authorization Require the runtime control plane to evaluate data sensitivity, source provenance and consent state before an agent can use information for a task.
Bottom line: Agentic AI changes the governance problem from who signed in to how a multi-step workflow is authorised before it acts.
Glossary terms: Agentic AI, Runtime Authorisation, Delegation Chain, Identity Knowledge Graph
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11/11/2026 6:06 pm
Agentic AI turns IAM from a point control into a moving control surface: The older model assumes the identity event is the main event. That assumption fails when a task can traverse several tools, services and agents before the system acts. The implication is that identity governance now has to evaluate execution paths, not just subjects.
A few things that frame the scale:
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems, according to the 2026 Infrastructure Identity Survey.
- 53% of security leaders expect AI to run major portions of their infrastructure autonomously within the next three years, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
A: Start by separating what an agent can access from what it can do on its own. Grant the minimum permissions needed, then increase autonomy in stages: explain, recommend, ticket, and only later remediate. Security teams should require business context, environment awareness, and approval gates for higher-risk actions, especially in production or externally facing systems.
👉 Read our full editorial: Agentic AI turns IAM into runtime policy over workflows