Gap Introduces AI Tools to Address Key E-Commerce Friction Points
Gap Inc. is rolling out two new AI-driven capabilities aimed at improving the online shopping experience: personalised sizing recommendations and checkout within AI-powered environments.
The initiative targets two of the most common barriers in apparel e-commerce — finding the right size and completing a purchase — as the retailer expands its use of artificial intelligence across customer journeys.
Personalised Fit Technology Moves Into the Purchase Flow
Gap is introducing predictive sizing powered by Bold Metrics, embedding fit recommendations directly into AI-driven shopping interactions.
Instead of relying on traditional size charts, customers will receive personalised guidance within conversational interfaces at the point of decision-making.
The company said this approach integrates sizing intelligence into what it describes as “agentic commerce”, where AI systems actively assist users throughout the shopping process.
Checkout Expands Into Google's AI Ecosystem
Gap is also enabling direct purchasing through AI-powered environments using Google's Universal Commerce Protocol.
This will allow shoppers to complete transactions within:
· AI Mode in Google Search
· The Google Gemini app
without being redirected to Gap's own website. Fulfilment and logistics will continue to be handled by the retailer.
A Shift Toward AI-Native Commerce Infrastructure
The move reflects a broader transition from traditional e-commerce models to AI-native commerce, where discovery, decision-making and checkout can occur within external platforms.
Gap said it has rebuilt its digital infrastructure to support this shift, including:
· Unified data systems built on Google Cloud
· AI-ready architecture across platforms
· Governance frameworks to manage AI deployment at scale
Executive Perspective
Sven Gerjets, chief technology officer at Gap Inc., said the strategy is focused on practical outcomes rather than experimentation.
“These partnerships are about solving real customer problems — helping shoppers feel confident about fit and making it easier to complete a purchase.”
He added that the company is scaling AI capabilities across the organisation to deliver measurable value over time.
Why This Matters for Retail
Gap's deployment highlights how retailers are beginning to integrate AI across multiple stages of the shopping journey, rather than applying it to isolated use cases.
Key implications include:
· Fit recommendation becoming a core conversion driver in apparel
· Checkout moving beyond retailer-owned websites
· AI platforms emerging as new commerce interfaces
As AI ecosystems such as search and assistants evolve, retailers may need to adapt their infrastructure to operate across both owned and third-party environments.
Source: Based on reporting from ChainStore Age