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02/09/2026 3:57 pm
TL;DR: Agentic AI is entering the same “magic first, governance later” phase that cloud did, except token spend and action fan-out are compounding faster, according to SecureAuth. The real issue is not only cost control but attribution at the control plane, because agent delegation chains change who acted, on whose behalf, and for what purpose.
NHIMG editorial — based on content published by SecureAuth: Agent costs will expose the control plane attribution gap
By the numbers:
- Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security.
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems.
- Systems with least-privileged AI access had a 17% incident rate vs 76% for over-privileged systems, meaning organisations failing to scope AI access properly are 4.5x more likely to experience a security incident.
Questions worth separating out
Q: How should teams govern agent fan-out before costs and privileges spread?
A: Start by treating the planner, sub-agents, and tool calls as one delegated identity chain.
Q: Why do agentic systems create both security risk and cost risk at the same time?
A: Because the same runtime behavior that consumes more tokens also expands authority across tools and downstream actions.
Q: What breaks when attribution is added after agent activity has already happened?
A: Post hoc attribution can show what was spent, but it cannot prove whether the agent was authorized to act or whether the delegated scope was appropriate at the moment of execution.
Practitioner guidance
- Define agent authority at the control plane Record which agent identities may initiate tool calls, spawn sub-agents, and expand execution scope before any runtime action occurs.
- Map delegation chains as identity objects Treat every planner, sub-agent, and tool invocation as a linked identity event with scoped permission and audit context.
- Separate usage reporting from authorization Use spend dashboards for finance visibility, but rely on runtime policy and audit records for governance decisions.
What's in the full article
SecureAuth's full article covers the operational detail this post intentionally leaves for the source:
- The delegation-chain examples that show how planner agents, sub-agents, and tool calls accumulate cost and authority.
- The control-plane framing SecureAuth uses to connect spend attribution with identity governance.
- The practical implications for teams trying to avoid retrofitted attribution after agent activity has already spread.
- The article's broader comparison between cloud FinOps lessons and agentic AI governance.
👉 Read SecureAuth's analysis of agent cost sprawl and delegation-chain attribution →
Agent cost sprawl and delegated action chains: what changes for IAM?
Explore further
02/09/2026 3:58 pm
Agentic AI will recreate the FinOps problem unless attribution is designed into identity from the start. The cloud lesson was not that spend was uncontrollable, but that organisations waited too long to connect usage to accountable identities and business purpose. The same mistake is now visible in agentic systems, where token spend and delegated action can spread across planners, sub-agents, and tools before anyone knows who caused what. The practitioner conclusion is simple: attribution cannot be an after-the-fact report in agentic environments.
A few things that frame the scale:
- Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security, according to The 2026 Infrastructure Identity Survey.
- Another finding from the same survey shows that 67% of organisations still rely heavily on static credentials despite the risks they pose to agentic AI deployments.
A question worth separating out:
Q: Should security teams manage agent spend and agent privilege together?
A: Yes, because separating them encourages blind spots. A high-cost agent chain often signals broad delegation, excessive tool reach, or poor scope boundaries. Managing spend and privilege together gives IAM and platform teams one view of how authority expands at runtime, which is exactly where agentic risk accumulates.
👉 Read our full editorial: Agent costs will expose the control plane attribution gap
