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01/07/2026 1:59 am
TL;DR: At Identiverse 2026, the dominant message was that AI agent security now hinges on ownership, discovery, and runtime authorization, with practitioners also debating how to prove after the fact what agents touched and who is accountable, according to Delinea. The broader lesson is that standing secrets and one-time trust decisions no longer fit agent behaviour, so governance must move to action-time control.
NHIMG editorial — based on content published by Delinea: What Identiverse 2026 made clear about securing AI agents
By the numbers:
- In most cases, they already do at almost 40 to 1.
Questions worth separating out
Q: How should security teams govern AI agents that act at runtime?
A: Security teams should govern AI agents through named ownership, complete discovery, and per-action authorization.
Q: Why do AI agents change traditional IAM and access review models?
A: AI agents change IAM because they can act faster than human review cycles and can touch tools or data without a stable operator at the keyboard.
Q: What breaks when AI agents are discovered too late or not at all?
A: When agents are not discovered early, teams cannot assign ownership, set scope, or prove what systems the agent can reach.
Practitioner guidance
- Inventory every AI agent before granting access Build a discovery process that finds agents created outside IT, links each one to a business owner, and records the systems and data it can reach.
- Require named human ownership for every agent Assign a responsible person who can approve scope, handle lifecycle events, and answer for misuse.
- Broker every tool call through a runtime policy layer Place an authorization point in the connection path so access is decided for each action and the live credential stays under central control.
What's in the full article
Delinea's full blog covers the operational detail this post intentionally leaves for the source:
- The specific runtime authorization pattern Delinea describes for keeping the live credential away from the agent.
- The operational framing for tying an AI agent to a named human owner and maintaining that relationship through lifecycle changes.
- The inventory and discovery considerations behind shadow AI visibility before access is granted.
- The connection-path architecture details that distinguish brokered access from simple policy checks.
👉 Read Delinea's analysis of how Identiverse 2026 shaped AI agent security →
AI agent identity at runtime: what Identiverse 2026 clarified?
Explore further
01/07/2026 2:17 am
Identity as the control plane is now the right framing for AI agents. The article reflects a broader market shift away from static access grants toward decision-time control, which is the only place agent behaviour can be governed reliably. For IAM and NHI teams, that means the unit of control is the action, not the account. This is the emerging operating model for AI agent governance.
A few things that frame the scale:
- 98% of companies plan to deploy even more AI agents within the next 12 months, despite documented rogue behaviour in 80% of current deployments, according to AI Agents: The New Attack Surface report.
- Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
A question worth separating out:
Q: Who should be accountable for AI agent access and misuse?
A: Accountability should sit with a named human owner who can justify the agent’s purpose, approve its scope, and respond if the agent behaves badly. Without that owner, the organisation cannot complete lifecycle governance or incident response with confidence. The owner record is the bridge between machine action and human responsibility.
👉 Read our full editorial: Identiverse 2026 shows why AI agent identity needs runtime control
