Topic starter
22/06/2026 9:53 am
TL;DR: AI agent adoption in Greater China is running ahead of understanding, with fewer than half of consumers able to identify an AI agent and 44% already reporting a negative outcome linked to use, according to SumSub. The governance problem is not capability alone, but whether users can verify delegated action and retain accountability.
Editorial analysis by NHI Mgmt Group, based on content published by SumSub: “Building Trust as AI Agents Take Hold: Greater China Survey Results”.
By the numbers:
- 44% across Greater China say they have already experienced at least one negative outcome linked to AI agent use.
Key questions
Q: How should security teams verify AI agents before allowing delegated actions?
A: Use a registration model that binds the agent to a responsible person or organisation, records its purpose, and issues a stable identity signal that can be checked at runtime.
Q: Why do AI agents create more risk than traditional automation?
A: AI agents create more risk because they can interpret context, choose actions, and invoke tools autonomously.
Q: What breaks when consumers cannot tell an AI agent from ordinary automation?
A: Delegation becomes unsafe because users may grant real authority to software they do not understand, and attackers can hide inside that confusion.
Practitioner guidance
- Define agent identity proofing requirements Establish what evidence is required before an AI agent can act on behalf of a user, including linkage to a responsible human or organisation, allowed scopes, and revocation conditions.
- Bound delegated permissions by action type Separate low-risk guidance from high-risk execution, and require explicit approval for payments, account changes, data sharing, and external-service access.
- Log every agent-initiated action with attribution Capture who authorised the agent, what it was allowed to do, which systems it touched, and whether the user approved or reviewed the action.
Bottom line: AI agent adoption in Greater China is revealing a governance gap between user willingness and user understanding, which makes verification a prerequisite for safe delegation.
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22/06/2026 10:32 am
Verification, not capability, is the trust control that now separates safe delegation from unsafe automation. The article shows that consumers are willing to use AI agents before they can reliably recognise them, which means trust is being built on assumed legitimacy rather than confirmed identity. That is a governance failure in waiting, because a delegated actor that cannot be verified cannot be safely authorised. Practitioner conclusion: treat verification as a prerequisite for agent-enabled access.
A few things that frame the scale:
- 19% of organisations give AI systems dramatically more access than human employees, nearly one in five granting unrestricted privilege, according to the 2026 Infrastructure Identity Survey.
- Systems with least-privileged AI access had a 17% incident rate vs 76% for over-privileged systems. Organisations failing to scope AI access properly are 4.5x more likely to experience a security incident, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: How should organisations secure payments when AI agents can buy on behalf of users?
A: They should separate user authentication, agent delegation, and purchase approval into distinct controls. That means phishing-resistant authentication for the human, explicit policy for the agent’s scope, and verifiable claims that the merchant can validate at transaction time. Without that separation, a delegated agent becomes just another opaque buyer with too much power.
👉 Read our full editorial: AI agent trust in Greater China depends on verification