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An AI shopping assistant can show you a different price from the one your friend sees because it may retrieve a different seller’s offer, account for a different location or delivery option, surface a promotion you are not eligible for, or display results at a different time. Retailers may also use personal information to tailor prices or offers. But a price difference alone does not show that the assistant itself changed the price—or that anyone was targeted.
First identify what is different
“The assistant showed a different price” can describe several things: the seller’s price, the offers the assistant found, a discount applied to one account, or the order in which results appeared. These are not interchangeable. An assistant can affect which offer you notice without setting the price charged by the retailer.
- Different seller or offer: The two results may come from different retailers or different marketplace sellers, even when the product name is the same.
- Different conditions: Location, delivery method, shipping, fees, taxes, time, inventory, or promotion eligibility can change the amount shown or the final checkout total.
- Different ranking: The assistant may select or order offers using filters, available data, or commercial criteria. A higher-ranked result is not necessarily the lowest final price.
- Personalized price or offer: A retailer may use information about a consumer to tailor a price, discount, or offer. Establishing that requires more than observing two different results.
Dynamic pricing and personalized pricing are not the same
Dynamic pricing
A seller may change prices over time or in response to factors such as demand or inventory. The Federal Trade Commission (FTC) says businesses may adjust prices on that basis as long as their pricing information is not misleading. A difference between two people who checked at different times can therefore have an ordinary market explanation.
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Personalized pricing
Personalized pricing uses information about a consumer or their behavior to tailor a price. Personalization can also affect which discount or offer is presented, without necessarily changing the base price. In January 2025, the FTC said staff had examined material from six companies and found that tracked behavior—from mouse movements to items left in an online cart—could be used by retailers to tailor pricing. The FTC described examples involving personal data, location, timing, sales channel, and inferred preferences. It also said the study was ongoing and that examples were hypothetical because the material was anonymized or aggregated; this is evidence of possible practices, not a controlled finding that an AI assistant charged two users different prices. Read the FTC’s January 2025 release.
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FTC staff reported that the intermediaries examined had at least 250 clients selling goods or services including groceries and apparel. That is a count of clients reported by FTC staff, not a prevalence rate for personalized prices or proof that every client used them.
What the assistant may change—and what is not established
An assistant can shape discovery: it may retrieve a different seller, omit some offers, or rank results differently. That can make the price a user sees differ even if the assistant does not set the seller’s price. Comparison tools in other sectors illustrate why ranking deserves attention: a 2024 Consumer Financial Protection Bureau circular describes compensation, consumer characteristics, product features, ratings, and other variables as possible influences on ordering in tools for consumer financial products. That analysis concerns financial products; it does not prove how retail AI shopping assistants rank products. Read CFPB Circular 2024-01.
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The available evidence does not establish that general-purpose AI shopping assistants routinely set different prices for different people, that any particular assistant passes personal data to a seller, or why a specific pair of users received different results. A discrepancy is a reason to compare the offer and its conditions—not, by itself, proof of personalized pricing.
How to compare two results fairly
- Match the item. Confirm the exact model, size, color, quantity, and other variant details. Similar product names can refer to different items.
- Match the seller. Check the retailer or marketplace seller identity, not just the assistant or marketplace name.
- Match delivery details. Use the same country, region, ZIP or postal code, and fulfillment method where possible. Delivery availability and costs can vary by location.
- Compare at roughly the same time. Note when each result was retrieved; prices and inventory can change.
- Compare eligibility and the final total. Check account status, loyalty membership, coupons, promotion terms, shipping, mandatory fees, taxes, and the amount at checkout. FTC guidance says discount eligibility and mandatory fees matter to the price that should be prominently shown. Read the FTC’s pricing and dark-pattern guidance.
- Identify what the result represents. Determine whether it is a seller quote, an estimate, a sponsored placement, or a commercial recommendation. A displayed recommendation may not be a neutral price comparison.
- Keep a record if the gap persists. Save screenshots, timestamps, seller details, and promotion terms. A difference that remains after controlling for these factors is more informative, but still does not establish its cause.
What the rules say depends on where you are
European Union
European Commission consumer guidance says traders must inform consumers when a price is personalized using automated decision-making and profiling of their behavior. The guidance also distinguishes discrimination based on nationality or residence from price differences grounded in objective factors, and notes that a seller may have different net prices across sales channels. It does not mean that every difference in price is unlawful. The page was last checked on April 30, 2026. For an unfair-pricing concern, it points consumers to national consumer associations or the European Consumer Centres network. Read the European Commission’s pricing guidance.
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United States
FTC materials distinguish adjustments based on demand or inventory from misleading price presentation. In August 2026, the FTC sought public comments on a draft enforcement policy statement concerning personalized pricing. The agency said undisclosed collection or use of personal data for personalized pricing could violate laws it enforces; then-chairman Andrew Ferguson said the FTC could not ban personalized pricing in every circumstance. The release set September 18, 2026, as the comment deadline, which has passed. This was a draft policy development, not a universal federal ban; policy status can change. Read the FTC’s August 2026 release.
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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
