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14/07/2026 4:24 pm
TL;DR: 61.5% of consumers have used AI for product discovery, yet 55.0% are not comfortable letting AI agents buy on their behalf and 50.8% assign responsibility for unauthorized purchases to the AI platform, according to Riskified’s Q1 2026 Agentic Commerce Pulse. The data shows agentic commerce is advancing faster than trust, authentication expectations, and accountability models.
NHIMG editorial — based on content published by Riskified: Consumer trust gap in agent-driven shopping, with Q1 2026 Agentic Commerce Pulse findings
By the numbers:
- 61.5% of consumers have used AI tools for product discovery and recommendations
- 55.0% are not comfortable with AI agents making purchases on their behalf
- 73.9% expect strong safeguards such as biometric or one-time password authentication
Questions worth separating out
Q: How should security teams govern AI agents that browse and transact on behalf of users?
A: Security teams should govern AI agents as delegated actors with narrow, task-scoped permissions, not as enhanced browsers.
Q: Why do AI shopping agents create accountability problems for merchants and platforms?
A: Because the person who benefits from the purchase, the platform that executed it, and the merchant that accepted it may all be different parties.
Q: What do organisations get wrong about biometric verification in agentic commerce?
A: They often treat biometrics as a blanket trust signal rather than a step-up control for specific risky actions.
Practitioner guidance
- Define explicit agent purchase boundaries Set hard policy for what an AI shopping assistant can do, including spend limits, merchant categories, and whether checkout can proceed without human confirmation.
- Require step-up verification for high-risk transactions Use biometric verification or one-time passwords when an AI-driven flow moves from discovery to checkout, especially for first-time merchants, unusual basket values, or changed delivery destinations.
- Log delegated intent and approval evidence Capture which identity initiated the task, which system executed it, what approvals were present, and whether a human confirmation was recorded before submission.
What's in the full report
Riskified's full article covers the operational detail this post intentionally leaves for the source:
- Question wording and survey segmentation across U.S. and U.K. consumers, useful for comparing market expectations.
- Full breakdown of consumer preferences for AI tools, retailer sites, and opting out of agentic commerce.
- The survey methodology behind the 2,000 respondent sample, including purchase recency and demographic framing.
- Riskified's discussion of merchant implications for fraud prevention and account liability.
👉 Read Riskified's survey on trust, fraud, and accountability in agentic commerce →
Agentic commerce trust gap: what merchants and IAM teams need to know?
Explore further
14/07/2026 4:32 pm
Agentic commerce creates an identity and liability boundary problem, not just a payment problem. Once an AI system can complete a purchase, the programme must decide whether the actor is the human, the platform, or the merchant flow. That distinction matters because fraud controls, consent capture, and post-incident accountability all depend on it. The practical conclusion is that commerce teams need explicit delegation policy, not just stronger checkout security.
A question worth separating out:
Q: Who is accountable when AI-assisted purchases lead to chargebacks or abuse?
A: The merchant remains accountable for most downstream business impact, including chargebacks, refunds, support costs, and inventory loss, unless the payment rail or wallet contract explicitly shifts liability. That means merchants, fraud leaders, and platform owners need governance controls before enabling agentic commerce at scale.
👉 Read our full editorial: AI shopping agents expose a trust gap in autonomous commerce
