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Give an AI shopping agent authority only inside a written, time-limited policy. Set a per-purchase ceiling, a rolling daily or weekly budget, a total task budget, allowed merchants and categories, shipping and geography rules, and an expiry time. Auto-approve only carts that satisfy every condition. Send expensive, unusual, recurring, regulated, or irreversible purchases to a person for fresh approval.
Enforce those rules with an agent-specific virtual card, payment token, or signed mandate. A human—not the agent—must create the credential, change limits, unfreeze or revoke it, and handle disputes. Deterministic checkout checks, complete audit logs, alerts, and a fast freeze function are as important as the dollar cap.
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Why do AI shopping agents need more than a spending cap?
An agent can interpret a request, search stores, select an item, and submit payment in seconds. That speed is useful, but an amount limit alone cannot tell whether the item is from an approved seller, contains an unwanted subscription, ships to the right place, or matches the user’s actual intent. A $200 cap could still permit a counterfeit product, an age-restricted purchase, or a recurring charge the user never meant to authorize.
Treat the agent as a bounded delegate. The policy should describe the job and all conditions under which the agent may act. The payment system should reject a transaction when any required condition fails, rather than relying on the model to remember a long instruction.
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- Intent: what the user asked the agent to accomplish and which products are in scope.
- Money: per-authorization, rolling-period, and total-task limits, with currency and tax treatment defined.
- Counterparty: permitted and blocked merchants, marketplaces, seller ratings if relevant, and product categories.
- Terms: delivery destination, shipping ceiling, return policy, warranty, and whether recurring billing is allowed.
- Time: when the authority starts and expires.
- Human gates: events that always require a person to approve again.
The UK Competition and Markets Authority (CMA) states that businesses remain responsible for an AI agent’s conduct even when another company supplied the agent: “When it comes to dealing with your customers, the same rules apply whether using AI or human agents.” Its 2026 guidance also says, “Ultimately, you will be responsible if an AI agent does something illegal.”
What limits should I set for an AI shopping agent?
Use several limits at once. A per-purchase cap controls the largest single authorization; a rolling budget limits cumulative exposure; a task budget prevents a long-running search from spending indefinitely; and an expiry window prevents an old instruction from remaining active.
Per-purchase authorization
Set the maximum amount for one checkout, and state whether it includes tax, shipping, tips, foreign-exchange fees, and deposits. For example, a policy could allow up to $75 including all charges, not $75 before tax. If the final total exceeds the cap, the payment must fail or return to a human for approval.
Rolling daily or weekly budget
A rolling period counts successful authorizations over the previous 24 hours or seven days, rather than resetting at an arbitrary calendar boundary. This limits damage if an agent repeats a purchase or splits one shopping task into many orders. Use a shorter window for consumables and a longer one for planned procurement, but keep the amount low enough that an error is tolerable.
Total task budget
Give each assignment its own ceiling. A “find replacement filters” task might have a total budget that is lower than the account’s general weekly budget. When the task budget is exhausted, the agent cannot continue by shifting purchases into another category or starting a new session.
Validity and expiry
Every mandate or token should have a start time and an expiry time. A one-off purchase can expire after checkout; a price-monitoring task might remain valid for a few days. Do not leave an open-ended authority attached to a standing card. Expiry should be enforced by the payment authorization layer, not merely displayed in the agent’s interface.
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Subscription and renewal limits
Recurring charges need a separate rule. Set a maximum initial price, a renewal cap, a maximum number of renewals, and an end date. Require fresh approval when the price, billing interval, merchant, or material terms change. A purchase that is acceptable once may be unacceptable when it repeats every month.
| Control | What it limits | What to specify |
|---|---|---|
| Per authorization | Largest single checkout | Amount, currency, tax and shipping treatment |
| Rolling period | Cumulative spend over time | 24-hour, seven-day, or other window and included transactions |
| Total task | Spend for one assignment | Task identifier, budget and what counts against it |
| Validity window | How long authority remains usable | Start, expiry and time zone |
| Renewal cap | Future recurring charges | Price, interval, number of renewals and reapproval triggers |
How should I choose an approval threshold?
Auto-approval should be the exception defined by matching conditions, not a blanket permission below a number. Require a fresh human decision whenever the amount is above the threshold or any risk signal appears.
Define a low-risk auto-approval band
Choose a ceiling that would not cause serious hardship if the item were wrong. Require every condition to match: approved merchant, allowed category, known delivery address, acceptable return terms, permitted payment rail, and no recurring commitment. If one field is unknown, route the cart to review instead of guessing.
Escalate by amount and novelty
Send a request to a person when the purchase exceeds the per-authorization threshold, uses a new merchant, falls into an unusual category, or materially changes shipping, warranty, or return terms. The approval screen should show the exact merchant, seller, items, quantities, taxes, shipping, currency, delivery date, return deadline, and whether the charge recurs.
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Always require approval for high-impact actions
- Regulated, age-restricted, or safety-critical goods.
- Irreversible purchases, deposits, tickets, or services with restrictive cancellation terms.
- Recurring commitments or any change to an existing subscription.
- Purchases outside the user’s stated geography or delivery constraints.
- Transactions that rely on a new payment rail, a new identity, or an unverified seller.
- Any cart that conflicts with the policy, even when its amount is small.
Approval must be current and specific. Do not let an agent reuse an approval for a different merchant, quantity, currency, or materially changed cart. For sensitive actions, use a trusted interface controlled by the user rather than an approval link supplied inside an untrusted page.
How do I stop an agent from changing its own limits?
Separate agent execution from credential administration. The agent may present a cart and request approval, but it must not be able to create payment credentials, increase limits, unfreeze a card, or access another card.
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Use an isolated payment credential
Issue an agent-specific virtual card, token, or signed mandate. Bind it to the agent identity, policy version, merchant and category restrictions, and expiry. Do not expose the primary card number or a wallet containing unrelated funds. If the provider supports network-level controls, enforce the restrictions there as well as in the agent software.
Keep administration human-only
Require a person or a separately controlled administrator to create the credential and change its limits. Place limit increases, category changes, merchant additions, unfreezing, and revocation behind strong authentication and an independent approval path. The agent should be unable to call those administrative functions, even if its prompt or session is manipulated.
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Provide a visible freeze and revoke control. Revocation should invalidate outstanding mandates or tokens and stop future authorizations; it should not depend on the agent cooperating. Record who revoked the authority, when, and why.
How should checkout verification work?
At checkout, compare the proposed transaction with the policy using deterministic fields. Verify the merchant identity, seller where available, cart contents, quantity, total, currency, shipping address, delivery method, return terms, recurrence, and remaining budget. A language model can explain the result, but a rules engine should make the allow-or-deny decision.
Use signed mandates for delegated purchases
Google’s Agent Payments Protocol (AP2) separates mandate delegation from action authorization. On a trusted surface, the user approves the constraints; a verifier then checks whether the proposed purchase is permitted. In autonomous mode, the agent produces a closed mandate only after finding a checkout that matches the approved constraint set. The protocol overview says, “The user’s signed approval must create a cryptographically signed ‘Checkout Mandate.’” A merchant can still require the user to return for confirmation.
Bind identity and intent to the payment
Mastercard’s agentic-token framework is designed to carry trusted-agent identity, purchase-intent data such as limits and validity windows, cryptographic tokens, and an audit trail. Those fields help a merchant and issuer determine what was authorized and provide evidence if a transaction is disputed. They do not replace your own category, budget, or approval policy.
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How do I implement a policy step by step?
Write the policy before granting payment authority, then test both successful and rejected paths.
- Describe the assignment. Record the user’s request, product categories, excluded categories, preferred and blocked merchants, geography, delivery constraints, and allowed payment rails.
- Set all money controls. Enter the per-authorization cap, rolling daily or weekly budget, total task budget, currency rules, and validity window. Add renewal caps and reapproval triggers for subscriptions.
- Define the approval matrix. List the conditions for automatic approval and every escalation trigger: amount, new merchant, unusual category, changed terms, recurring billing, regulated goods, and irreversible actions.
- Create an isolated credential. Have a human issue the virtual card, token, or mandate with the policy attached. Confirm the agent cannot see or use unrelated payment instruments.
- Run deterministic preflight checks. Before authorization, compare merchant, seller, cart, amount, currency, shipping, terms, recurrence, remaining budget, and expiry against the policy.
- Present human approvals clearly. Show the complete cart and consequences on a trusted surface. Bind the approval to the exact cart and policy version so it cannot be silently reused.
- Log every event. Store user intent, policy version, agent identity, mandate or token, cart, merchant, approval event, authorization response, and receipt.
- Test failures. Simulate an over-limit cart, blocked merchant, changed price, expired mandate, duplicate order, currency mismatch, and attempted administrative action. Verify that each is denied or escalated.
- Operate the recovery path. Keep a human freeze and revoke control, alert on suspicious patterns, and define who investigates complaints, refunds, and disputes.
What do current agent-payment approaches control?
The following comparison uses the controls publicly described for each approach. “Not stated” means the cited description does not establish that feature; it is not evidence that the feature is absent.
| Approach | Delegation and identity | Limits and approval | Credential safeguards | Evidence or coverage noted |
|---|---|---|---|---|
| AP2 | User-approved constraints and signed checkout mandates; verifier checks the proposed purchase | Autonomous mode closes only a matching constraint set; merchants may require user confirmation | Cryptographically signed mandate on a trusted surface | Protocol model; specific geographic availability not stated |
| Mercury agent cards | Human creates cards and assigns them to agents | Daily, weekly, or monthly limits | Agents cannot create cards, change limits, unfreeze cards, or access unassigned cards | Provider feature description; eligibility and current availability should be checked |
| Anima virtual cards | Virtual-card controls tied to a program | Per-authorization and daily limits, merchant-category restrictions, optional pre-approval rules | Production issuance requires KYB approval | Program eligibility and geography not stated |
| Mastercard agentic-token framework | Trusted-agent identity and purchase intent travel with the token | Intent can include limits and validity windows | Cryptographic token and audit trail | Framework description; payment-rail rollout and geography vary |
| Federal Reserve framing | Distinguishes human-controlled agent-assisted commerce from constrained agent-delegated commerce | B2B procurement can use approved suppliers and budgets; larger values increase exposure | Calls for robust controls and monitoring rather than a particular credential | Conceptual and supervisory perspective; no product availability claim |
What should I monitor after an agent is authorized?
Monitoring catches failures that a pre-check cannot. Alert when spending approaches a limit, declines repeat, a policy mismatch occurs, a new merchant appears, or a user complains. Review authorization and receipt data together so you can distinguish a declined attempt from a completed but incorrect order.
Keep an audit trail that can answer five questions
- What did the user ask for, and which policy version interpreted that request?
- Which agent identity, token, mandate, and credential acted?
- What cart, merchant, currency, shipping terms, and total were presented?
- Who approved it, when, and on which trusted surface?
- What did the issuer return, and what receipt or refund followed?
Freeze first, investigate second
If an agent behaves unexpectedly, freeze its credential immediately, revoke outstanding mandates, and preserve logs. Then check whether the problem was a misunderstood instruction, a merchant-side change, a duplicate request, credential compromise, or a policy implementation bug. Contact the merchant and issuer through their normal dispute channels, and restore authority only after testing the corrected rule.
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| Symptom | Likely cause | Fix |
|---|---|---|
| Several small orders exhaust the budget | No rolling or task-level cap | Add both controls and count all successful authorizations, including split carts |
| Agent buys from an unwanted seller | Only an amount cap was configured | Add merchant or seller allowlists and require escalation for unknown merchants |
| “One-time” purchase becomes recurring | Renewal terms were not checked | Block recurrence by default; set renewal caps and reapproval on price or term changes |
| Checkout total changes after approval | Approval was not bound to final cart data | Re-run deterministic checks and obtain approval for the changed cart |
| Agent appears able to raise its own allowance | Administrative API is exposed to the agent | Remove that permission, rotate credentials, and require a separate human administrator |
| Dispute cannot be reconstructed | Missing intent, policy, or receipt records | Log the full authorization chain and retain it under your applicable retention policy |
| Old authority keeps working | No enforced expiry or revocation propagation | Use short validity windows and verify that freeze and revoke invalidate outstanding tokens |
What are the legal and operational responsibilities?
The business deploying or accepting an agent remains accountable for consumer-protection obligations. The CMA calls for training agents to respect consumer rights, transparent disclosure of AI use and limitations, testing, regular monitoring, human oversight, audit logs, and rapid remediation. Its consumer analysis also identifies mandatory confirmation for high-risk actions, clear disclosure of incentives and affiliations, and escalation and resolution processes.
Do not describe an agent as fully autonomous if a person must approve key actions, and do not hide commercial incentives or merchant relationships. Keep records sufficient to explain why a transaction was allowed and how a complaint was resolved. Requirements differ by jurisdiction, product category, and payment arrangement, so obtain local legal advice for regulated or cross-border use.
How mature is agentic shopping?
It is an early-stage capability with standards and controls still evolving. Visa reported a 4,700% increase in AI-driven traffic to U.S. retail sites in 2025 when announcing its Trusted Agent Protocol. That is an industry-reported traffic statistic, not evidence that autonomous purchasing is broadly adopted. Independent consumer-adoption, fraud-rate, and loss-rate figures were not established in the cited official material.
Federal Reserve Governor Christopher Waller identified trust as the central scaling problem for delegated commerce: “The biggest barrier to scaling agentic commerce, particularly the agent-delegated model, is building sufficient trust among buyers and sellers.” Start with low-value, reversible tasks and expand authority only after your controls, logs, and recovery drills work in practice.
What should a practical policy look like?
Use a machine-readable policy or an equivalent form that a rules engine can enforce. The following illustrates the fields to complete; replace the example values with your own risk limits.
Task: buy replacement air filters for the office printer
Allowed categories: printer consumables
Blocked categories: subscriptions, gift cards, regulated goods
Merchant rule: approved suppliers only; unknown merchants require approval
Per-authorization cap: 75 USD including tax and shipping
Rolling budget: 200 USD in any seven-day window
Total task budget: 300 USD
Validity: 2026-10-26 09:00 through 2026-11-02 09:00 UTC
Auto-approval: only when every rule matches and no recurring charge exists
Human approval: amount above 75 USD, changed return terms, new merchant, or any recurrence
Credential: agent-specific virtual card; no limit changes or unfreeze permission
Revocation: human-controlled freeze and revoke available at all timesThe example is a format, not a universal dollar recommendation. Your threshold should reflect the value of the goods, the user’s ability to absorb a loss, and the consequences of an incorrect or recurring purchase.
Frequently Asked Questions
Can I let an AI agent use my normal credit card?
It is safer not to expose a primary card that holds unrelated funds or has a high standing limit. Use an isolated virtual card, token, or mandate whose scope and expiry can be revoked without disrupting other payments.
Should approval be required for every purchase?
Not necessarily. Low-value, reversible purchases can be auto-approved when merchant, category, cart, delivery, terms, and budget all match. Requiring confirmation for high-impact or unusual transactions preserves convenience without granting unrestricted authority.
What evidence do I need if an agent buys the wrong item?
Retain the original user request, policy version, agent and credential identity, final cart, merchant, approval event, authorization response, and receipt. That chain helps you determine whether the error came from interpretation, checkout changes, credential misuse, or a merchant dispute.
How often should agent spending policies be reviewed?
Review them whenever the agent, payment provider, merchants, product categories, or applicable rules change, and after any incident or complaint. A short scheduled review—such as monthly for active programs—can catch stale merchants, expired assumptions, and unused permissions.
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