Hardware-backed approval for AI agents exposes the accountability gap

At a glance

What this is: NHI Mgmt Group's analysis, drawing on Yubico's blog post: At RSAC 2026, agentic AI security hinged on cryptographically verified human approval and simpler passwordless onboarding for human identities.

Why it matters: IAM and PAM teams need to see how AI-agent approvals, workforce enrollment, and accountability controls intersect, because the control gap is now between authorisation intent and provable execution.

Context

Agentic AI creates a governance problem that standard approval workflows were not built to solve. If a system can initiate a high-consequence action and a human later claims oversight, the programme still has to prove who approved what, when, and for which actor.

This article is about the accountability boundary between AI agents and the humans who authorise them, with passwordless identity and YubiKey enrolment appearing as adjacent human IAM topics. The central issue is not convenience, but whether approval can be cryptographically tied to a specific decision and identity.

RSAC 2026 is the conference context, not the subject. The subject is how organisations establish trustworthy approval semantics for AI-driven action while keeping human identity enrolment and recovery workable at scale.

Key questions

Q: Who should approve high-risk actions taken by an AI agent?

A: A verified human should approve high-risk agent actions before execution, especially where money, sensitive data or privilege changes are involved. Approval should be coupled with liveness validation and logged context so the organisation can prove the decision was intentional and attributable.

Q: Why do passwordless systems still need identity governance?

A: Passwordless systems still need identity governance because authentication strength does not answer lifecycle questions. Teams still need to decide who can enrol devices, how to revoke lost authenticators, how to prove ownership during recovery, and when fallback access is acceptable. Strong login technology without governance often produces hidden exceptions that are hard to audit.

Q: What breaks when AI actions are not bound to a human approver?

A: Without a verifiable human approval step, high-consequence AI actions become difficult to attribute, contest, or reconstruct after the fact. Audit logs may show activity, but not durable intent. That gap weakens accountability in both security and compliance programmes, especially when the action crosses data, infrastructure, or privilege boundaries.

Q: What is the difference between authentication and authorisation in agentic AI governance?

A: Authentication proves who or what is present, while authorisation proves whether that identity is allowed to perform a specific action. In agentic AI, both matter, but authorisation becomes more important because the system can act at runtime. A secure login alone does not establish that the agent’s next action was approved.

Technical breakdown

Why approval binding matters for AI agents

A human approval workflow only creates accountability if the approval is bound to the exact action, the actor receiving authority, and the moment of execution. In agentic AI, that matters because the system may translate intent into actions after the original request context has shifted. If approval is logged separately from execution, the organisation may know a human agreed in principle but still be unable to prove that the agent action was authorised. That is an identity problem, not just an audit problem.

Practical implication: bind approval records to the agent action, not just to the request or ticket.

Hardware-backed proof of presence for human authorisation

Hardware-backed proof of presence uses a physical authenticator to strengthen the link between a person and an approval event. In practice, that reduces the chance that an approval is detached from the person who made it or replayed later in a weaker form. For AI agents, this is useful only if the approval step is part of the control path that governs the agent’s action, rather than a generic login ceremony. The control value comes from cryptographic binding, not from stronger user experience alone.

Practical implication: require phishing-resistant human confirmation for high-consequence AI actions.

Passwordless enrollment still needs lifecycle governance

Passwordless identity reduces password risk, but it does not remove the need to govern issuance, recovery, and enrollment. When organisations pre-register hardware keys or streamline onboarding, they are shifting trust into the registration and recovery steps. That means the real control question becomes who can enroll, who can recover, and how those events are tied to employment or role change. If those lifecycle steps are loose, passwordless adoption can improve authentication while leaving governance gaps untouched.

Practical implication: treat enrollment and recovery as governance events, not administrative chores.

NHI Mgmt Group analysis

Approval without cryptographic binding is not accountability. The article exposes a familiar governance error: organisations often treat workflow approval as evidence of authorisation even when the approval is not bound to the exact AI-driven action. That assumption is brittle in agentic systems because the actor can separate request, approval, and execution across different moments and contexts. Practitioners need to stop treating generic sign-off as sufficient proof of authority.

Proof of presence becomes the control plane for high-consequence AI actions. Once an agent can act on behalf of a business process, the important question is no longer whether a person was somewhere in the loop, but whether the human’s presence was cryptographically established at the moment authority was granted. That shifts the control conversation from process documentation to event-level assurance. The practical conclusion is that approval semantics must be machine-verifiable.

Identity enrolment and recovery are part of AI governance now. The passwordless and YubiKey enrolment pieces matter because the same lifecycle machinery that secures humans also determines who can authorise or recover access used in AI-assisted workflows. If enrolment and recovery are weak, approval chains inherit that weakness. The programme implication is to govern identity lifecycle as a shared control layer across human and AI-enabled execution.

AI agent accountability is creating a new identity governance pattern: the approval chain. Traditional IAM asks who can sign in, but agentic AI asks who can authorise action and how that decision is proven later. That is a distinct governance layer that sits above authentication and below execution. Teams should treat the approval chain as a first-class control object alongside privilege and authentication.

What this signals

Approval chains are becoming a distinct identity control surface. As organisations put AI agents into real workflows, the important governance question is no longer just who can authenticate. It is who can authorise a consequential action, how that decision is tied to a person, and whether the evidence survives later review.

Hardware-backed proof of presence changes the assurance model. The control value is not in the authenticator alone, but in making human approval harder to separate from the action being approved. That pushes security teams to redesign workflow controls around non-repudiation, not around convenience.

Passwordless programmes must now be judged by lifecycle integrity. If enrolment, recovery, and device reassignment are weak, the organisation may reduce phishing risk while preserving a broader governance gap. The practical signal is that identity lifecycle controls and AI approval controls are converging.

For practitioners

• Define a high-consequence approval policy for AI agents Identify which agent actions require a cryptographically verified human authorisation step, and distinguish those from low-risk automated actions.
• Bind approval evidence to the exact action Capture the actor, action payload, timestamp, and approver identity in one tamper-resistant record so approval cannot drift from execution.
• Review enrollment and recovery governance Treat hardware key enrolment, re-enrolment, and account recovery as controlled lifecycle events with explicit ownership and auditability.
• Map AI workflow approvals to accountable owners Assign a business approver for each AI workflow that can trigger consequential actions, and ensure the approval path is documented and testable.

Key takeaways

• The article frames agentic AI governance as an accountability problem, not just an authentication problem.
• Cryptographic proof of human approval matters because generic sign-off is too weak for high-consequence AI actions.
• Passwordless adoption remains useful, but only if enrolment and recovery are governed as lifecycle controls.

Key terms

• Approval Chain: The sequence of reviewers who validate a request before access is granted. Approval chains can improve oversight, but only when each approver has enough context to judge the risk, scope, and business need. Otherwise, the chain documents consent without proving that the entitlement is properly authorised.
• Proof of Presence: A verification approach that aims to establish that a real person is actively participating at the moment of authentication. It goes beyond matching a stored trait and instead looks for live, context-specific evidence that resists replay, cloning, and remote fabrication.
• Passwordless Identity Assurance: Passwordless identity assurance is the degree to which an authentication programme can verify a user without relying on passwords as a routine or fallback method. In practice, it depends on the reliability of biometrics, device binding, recovery, and exception handling across the full enterprise estate.
• Agentic AI: Autonomous AI systems capable of planning, deciding, and taking actions, including calling APIs, writing code, and orchestrating other agents, with minimal human oversight. Agentic AI introduces new NHI risks as agents must authenticate to external services.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building or maturing an IAM programme, it is worth exploring.