Gap brings conversational AI to online shopping
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Gap Inc. is adding AI-powered shopping tools across its brands as retailers test whether conversations can replace some of the search boxes, filters and product grids that have defined ecommerce for decades.
The company announced the new experiences Oct. 5, 30 years after Gap launched its first ecommerce website.
Gap customers can now use third-party platforms Alta Daily and Daydream to find clothing. Alta Daily can recommend outfits based on factors such as a customer’s schedule, budget and local weather. It can also combine products from retailers with clothes the user already owns.
Daydream takes a different approach. Shoppers can describe what they want in everyday language and receive fashion suggestions from across Gap Inc.’s brands, including Gap, Old Navy, Banana Republic and Athleta.
Old Navy and Banana Republic are bringing conversational shopping directly to their websites and apps. Customers can describe what they are looking for instead of relying only on product categories or search terms.
The launches place Gap among a growing number of retailers testing how generative AI could change product discovery.
There is a clear commercial reason to pay attention. AI is sending more shoppers to retail websites, and those visitors are showing signs of becoming valuable customers.
AI is becoming a measurable source of retail traffic
AI-driven shopping is still at an early stage, but traffic patterns are becoming harder for retailers to ignore.
Adobe found that AI-referred traffic to US retail websites rose 393% year over year during the first quarter of 2026. By March, shoppers arriving through AI sources converted 42% better than other traffic.
Those visitors also spent 48% longer on retail websites and viewed 13% more pages per visit.
That was a major change from March 2025, when AI traffic converted 38% worse than other sources.
The figures suggest AI services are starting to influence buying decisions before customers reach a retailer’s website. A shopper may ask an AI service to compare products, find options within a budget or suggest clothing for a specific event. By the time the shopper reaches the retailer, much of the early research may already be complete.
This creates a new challenge for ecommerce teams.
For years, retailers have designed websites around customers who arrive through search engines, advertising, social media or direct visits. They have also built internal search tools around keywords and categories.
Conversational shopping changes that model. Instead of searching for “women’s black jacket,” a customer might ask for a lightweight black jacket that works for a business trip to London next week.
The retailer then needs product information that is detailed and accurate enough to answer that request.
Gap has already been preparing for that shift. Earlier this year, the company announced new AI-based fit features and support for Google’s Universal Commerce Protocol, an open standard designed to help AI agents interact with retailers and commerce systems.
Together, those moves suggest AI shopping is becoming part of Gap’s wider ecommerce strategy rather than a single test.
Trust will shape how far shoppers let AI go
Better product discovery does not mean customers will hand more of the shopping process to AI without question.
Research from Synchrony and Oxford Economics shows consumers place security and control ahead of convenience when deciding whether to use AI for shopping.
In a 2026 study of US consumers, 82% said keeping their data secure was important. Another 77% wanted transparency about how their information was used. Saving time ranked lower, at 58%.
Consumers were also more comfortable with AI handling lower-risk tasks.
Some 79% were willing to let AI automatically apply discounts, while 74% were willing to let it use loyalty points or rewards. Only 43% were comfortable allowing AI to make purchases up to a preset spending limit.
Existing relationships also mattered. The study found that 56% of consumers would be likely to trust an AI shopping assistant provided by a retailer or brand.
That could work in Gap’s favor. Its brands already have customer relationships, purchase histories and loyalty programs that newer AI shopping services do not.
But fashion presents another problem because recommendations are highly personal.
A SmartCustomer survey cited by Retail Dive found that 45% of purchases consumers regretted making with AI assistance involved apparel and footwear.
Fit, color, style, occasion and personal taste all affect whether a shopper sees a recommendation as useful.
That raises the stakes for retailers. An AI tool designed to make shopping easier can create more work if its suggestions do not match what the customer wanted.
Retailers may need to rethink product discovery
Gap’s latest launch points to a wider change in what retailers may need from their ecommerce systems.
The traditional online store asks shoppers to understand its structure. Customers choose a category, enter search terms and apply filters until the range becomes manageable.
Conversational commerce changes part of that process. The customer explains the need, and the system is expected to understand the request.
That puts more pressure on the information behind every product.
Accurate sizing, color, materials, price, stock availability and product descriptions become important inputs for AI systems trying to match customers with the right items.
Retailers may also need to reconsider where product discovery begins.
Some customers will still start on a retailer’s website. Others may begin with general AI assistants or specialist shopping services, then reach the retailer much later in the buying process.
That could make visibility within AI recommendations another part of ecommerce strategy alongside search, paid media and social channels.
There are limits to how quickly that shift can happen. Consumers still want control, especially when money and personal data are involved. Retailers also need to show that AI recommendations are accurate enough to be useful.
Gap’s experiment matters beyond the technology itself.
Its first ecommerce website helped move product discovery from stores to screens. Thirty years later, the company is testing whether the next change will move shoppers from searching for products to simply describing what they need.
Source:
Retail Dive
