Nearly one-quarter (24%) of Canadians say they have already allowed AI to effectively make a purchase decision for them, with a further 37% willing to let AI automatically select products based on their preferences (Retail TouchPoints). Overall, 54% of Canadians trust information from AI platforms, rising to 77% among weekly AI users (Retail TouchPoints). This shift represents a fundamental change in how retailers influence purchase decisions—AI is now a second decision-maker alongside the customer.
Consumers are developing detailed, personalized shopping prompts that encode their aesthetic preferences, budget constraints, and style values in ways traditional product filters cannot capture. Products may be screened by AI before a customer ever sees a retailer's category page or promotional banners, meaning exclusion from an AI-generated shortlist leaves a brand with little opportunity to change a customer's mind (Retail TouchPoints). For commerce practitioners, this demands a rethinking of product data architecture—information must now satisfy both search engines and AI interpretation systems, capturing nuanced attributes like design language and quality signals that live in reviews and imagery rather than structured fields.
Physical stores face a pivotal role: as AI handles routine replenishment decisions, in-store experiences become places where customers discover and refine preferences they later encode into their AI prompts (Retail TouchPoints). Established brands may benefit from familiarity bias in AI recommendations, while challenger brands must compete on price, reviews, or feature fit to enter the shortlist. Retailers should immediately research how their customers currently use AI in purchase decisions, which preferences they share with systems, and where they still value in-store discovery.