iProov for Agentic AI

How humans control AI agents acting on their behalf is the focus of iProov’s work in Agentic AI. Our approach centers around confirming that an accountable human approved the most consequential decisions, even where the ultimate action is performed by an AI agent.

iProov does this by attaching an individual’s identity to a specific agentic transaction, creating verifiable evidence that the correct person approved each action. Routine work can remain autonomous, while high-risk actions require accountable human authorization.


Jumping In

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What is Agentic AI? How Does it Work?
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What Makes Human Authorization ‘“Agent-Resistant”?

Which Actions Require a Human “in-the-loop”?

Frequently Asked Questions

Discuss iProov Agentic AI Technology and Solutions

Have an unanswered question?

Contact our internal lead on Agentic AI and iProov representative at the FIDO Agentic Authentication Technical Work Group, Oliver Rodwell, for further discussion:

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Comparison of AI identity management benefits

 

What Is Agentic AI?

Agentic AI refers to artificial intelligence systems that can pursue a goal, plan a sequence of steps, and take the necessary actions to fulfill that goal by using digital tools, applications, or services. They exert unprecedented autonomy and are often deployed with limited human intervention or oversight.

What Makes Human Authorization Agent-Resistant?

Agent-resistant authorization is designed so that an AI agent cannot generate, reuse or redirect the proof required to approve its own action.

  • Human-originating input

    A fresh biometric check establishes the presence and identity of the human approver using evidence that an AI agent cannot produce.

  • Independent approval channel

    The transaction details reach the approver outside the agent-controlled workflow, and the decision returns directly to the system, enforcing the action.

  • Action-bound evidence

    The approval is bound to the precise transaction. If a material detail changes, a new decision is required.

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Which Actions Require Human Authorization?

Human approval should correspond to the risk and consequence of the action.

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Agentic AI: Industry Context & Statistics

ADOPTION INTENTIONS

17% of organizations have already deployed AI agents, while over 60% anticipate deploying them within two years.

Gartner’s 2026 CIO and Technology Executive Survey

GOVERNANCE READINESS

21% reported mature governance for agentic AI; 74% of organizations expect to use AI agents at least moderately by 2027.

Deloitte’s 2026 State of AI in the Enterprise research

HUMAN AUTHORISATION

Action risk (63%) and human authorisation (53%) were identified as leading signals informing the governance of AI agent behaviour.

CSA’s Token Security-sponsored survey

Explore our Agentic AI Research and Insights

Visit our resource library for articles, case studies, reports, press releases, and more.

Assuring Human Approval of Agentic AI Actions

Delegating Judgment: The Case for Verified Human Authorization in Agentic AI

Governing the High-Risk Actions of AI Agents

More Resources

Frequently Asked Questions (FAQs)

Biometric liveness does not secure every component of an AI agent’s operation; it secures a single, but nonetheless critical, set of moments in its management lifecycle. Specifically, the moments at which consequential actions require human input. Biometric liveness supplies fresh evidence from a physically present person proving their involvement in an approval process.

No. The permissioning system determines what an agent may do and when approval is required. iProov provides strong evidence that the nominated person was genuinely present and approved the specific action.

Record approval as a transaction-specific receipt identifying the agent, action, approver, decision, applicable policy, assurance method and time. Any material change to the action should invalidate the receipt and require a new approval.

A step-up control requiring a nominated person to approve a specific action before an agent proceeds. iProov contends that for high-risk actions, a valid credential is not enough, because the process must also establish the identity and genuine presence of the person approving. The control should show authoritative transaction details directly to the approver, capture an affirmative decision using evidence the agent cannot satisfy independently, and return that decision directly to the system enforcing policy.

Agent identity answers which agent is acting: a distinct entity with its own credentials, standing permissions, and an accountable owner. Human authorization answers a different question, which is whether a specific person approved a specific action. An organization can have excellent agent identity and still be unable to evidence that anyone authorized a given transaction. The two are complementary, and many deployments today address neither directly.


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