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AI-driven retail traffic is a broad term for shopping activity that starts with or is influenced by an AI tool. It can mean an assistant helps someone compare products, sends that person to a retailer’s site, or—when the technology and permissions allow—acts on the shopper’s behalf. Those are different stages: more AI-referred visits do not, by themselves, prove that agents are completing purchases or creating incremental sales.
What counts as AI-driven retail traffic?
The term covers several related but distinct events. An AI assistant may help a shopper research a product without sending them to a store; it may recommend an item and refer the shopper to a retailer; or it may carry out more of the transaction for the shopper. The first two are already part of how people discover products. The last—delegating a purchase to an agent—is a more advanced and separate behavior.
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- AI-assisted discovery: a person asks for recommendations, product comparisons, reviews, or deals and remains in control of the search.
- AI referral traffic: a shopper follows a link or recommendation from an AI chat or other AI-powered experience to a retailer.
- Agent-completed transactions: software takes actions toward buying, potentially with the shopper’s authorization. A referral visit is not evidence that this happened.
These measures have different denominators. A survey about using an AI tool, a platform count of visits referred by AI, and a count of purchases completed by agents cannot be treated as interchangeable statistics.
What the latest figures show—and what they do not
Recent findings indicate that AI is becoming a more common part of product discovery, but they do not establish that it dominates retail traffic or that shoppers are routinely handing over entire purchases.
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| Finding | What was measured | How to read it |
|---|---|---|
| Salesforce reported 200% year-over-year growth in agentic search as the first step in the shopping journey. | Salesforce’s September 30, 2026 release; its analysis also found AI-chat referral traffic grew 150% to 428% year over year in every measured quarter from Q1 2024 through Q1 2026, across more than 1.5 billion shoppers in 37 countries. | These are growth figures for AI-related activity, not the share of all retail visits or proof of incremental sales. Overall traffic grew at single- to low-double-digit rates in the same analysis. Salesforce’s release describes the scope and findings. |
| 51% of U.S. consumers said they had used at least one AI-powered tool to support shopping in the past month. | NielsenIQ’s September 24, 2026 U.S. monthly tracker, based on approximately 500 consumers. | This is self-reported tool use, not a finding that 51% delegated purchases to agents. NIQ’s release reports the sample and measure. |
| 41% used AI assistants to research products, 33% to look for reviews, and 31% to search for deals. | IBM consumer research summarized by the National Retail Federation in 2026. | The activities describe assisted shopping, not necessarily visits or purchases. NRF/IBM’s summary also discusses consumer concerns. |
The percentages above come from different studies, geographies, methods, and time windows. They should not be combined into a single estimate of AI’s share of shopping. In particular, a large percentage increase can arise from a relatively small starting volume; growth in referred visits does not show whether those visits are new customers, would otherwise have arrived through another channel, or become completed orders.
How AI changes the shopper’s path to a product
Research, comparison, and recommendations
A shopper can describe a need in ordinary language—such as a budget, use case, or preferred features—and ask an assistant to narrow the options. AI tools can also help surface reviews and compare products. Amazon describes Alexa for Shopping, the experience it called Rufus before May 13, 2026, as a collection of conversational, visual, and auditory discovery tools. Any usage or conversion figures Amazon publishes about the feature are its own claims, rather than independent measures of the whole retail market. Amazon explains Alexa for Shopping.
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From an answer to a retailer visit
If an assistant presents a product or retailer link and the shopper follows it, that visit can be recorded as AI referral traffic. The assistant may have influenced discovery even when the shopper later checks other sites, uses a retailer’s own search, or changes their mind. Referral counts therefore describe one point in a journey, not the whole path from consideration to purchase.
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When the assistant acts for the shopper
Agentic commerce refers to software doing more than answering questions—for example, carrying out shopping actions on a person’s behalf. The extent of delegation matters: a recommendation, a pre-filled cart, and an authorized completed order are not the same outcome. The available traffic and survey figures do not establish that a shopper has granted an agent authority to complete a purchase.
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What online shoppers should check
AI can reduce the effort of finding and comparing options, but the shopper still needs to decide whether a recommendation is accurate and suitable. Before buying, verify the details that affect the actual order:
- Product specifications, compatibility, size, and included accessories.
- Current price and whether discounts or fees apply.
- Availability and delivery date for the selected retailer and location.
- Return conditions and any other terms that matter if the item is unsuitable.
- Whether the recommendation reflects your needs, rather than a preference or purchase-history signal you did not intend to use.
Privacy and control remain relevant because assistants may use personal preferences or shopping history. NRF/IBM’s 2026 summary identifies overlapping concerns about privacy, misuse, and unwanted marketing. Walmart’s 2025 Retail Rewired report found that 46% of respondents were somewhat or very unlikely to use a digital assistant or agent for an entire shopping trip; that result is a measure of reported reluctance in Walmart’s research, not a universal estimate of all shoppers. Walmart’s report provides that context.
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What retailers should do as discovery shifts
When shoppers begin in an AI chat, a retailer may have less control over the initial product comparison. The practical response is to make product information dependable wherever it is consumed, while continuing to serve people who use traditional search and retailer-owned experiences.
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- Test conversational language: check whether product descriptions answer natural-language questions shoppers might ask, as well as conventional keyword queries.
- Measure the whole path: distinguish AI exposure and referred visits from completed orders, and assess whether the channel adds customers or shifts attribution from another source.
- Preserve other discovery routes: traditional search remains important. Walmart’s 2025 research found traditional methods still led shopper discovery, alongside the reported reluctance to delegate a full shopping trip.
Salesforce’s September 2026 release describes retailer investment in product-content quality, conversational queries, AI search feeds, and natural-language descriptions. It also identifies fragmented data and inconsistent omnichannel information as obstacles. Salesforce’s findings are a report of organizational actions and platform analysis, not a guarantee that any particular optimization will increase sales.
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How to interpret claims about AI’s retail impact
When comparing an AI-shopping statistic with another, check four things before drawing a conclusion:
- The event: Is the figure about reported use, AI-assisted discovery, a referral visit, or an agent-completed transaction?
- The denominator: Is it a share of surveyed people, a count of visits, or a growth rate from a prior period?
- The scope: Which country, population, retailers, or platform activity does it cover?
- The period and method: Is it a monthly consumer survey, a multi-quarter platform analysis, or another measure?
For example, Salesforce’s multi-country referral analysis and NIQ’s monthly U.S. consumer survey measure different things. Neither, alone, shows that AI creates incremental sales. A claim about sales impact needs evidence linking AI exposure to completed purchases and accounting for what those shoppers would otherwise have done.
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