Clothes Shoppers Show Limited Interest in AI Tools

YouGov published new polling of U.S. adults who shop for clothing that measures receptiveness to AI across the shopping journey. Per YouGov, shoppers place low priority on AI for discovering new clothing: only 6% said they would use general AI tools like ChatGPT or Gemini for discovery, and 6% said they would use AI chat tools embedded in retailer sites or apps. Reported preferred discovery channels are in-store browsing (60%), retailer websites or apps (46%), and recommendations from friends or family (40%).

YouGov also asked about discrete AI use cases. The most-cited interest areas were product availability or stock checks (26%), size and fit recommendations (25%), and product discovery based on preferences (21%). Fewer clothes shoppers expressed interest in AI-driven styling or outfit suggestions (16%). YouGov notes younger cohorts, specifically Gen Z and Millennials, show slightly higher interest in AI discovery than older cohorts, but even among younger shoppers AI discovery remains behind established channels.

Industry-pattern observations: Consumer surveys of AI in retail commonly show stronger uptake for pragmatic, transactional features than for creative or discovery uses. Practical features such as stock checks and fit guidance map to measurable friction points (availability, sizing uncertainty), which often yield clearer conversion or support-cost benefits compared with broader recommendation systems that rely on trust and personalization.

Industry observers often point out that adoption of AI features in consumer retail depends on perceived accuracy, privacy tradeoffs, and visible benefit. The YouGov numbers align with prior surveys where modest shares adopt new interaction modes until retailers demonstrate reliable outcomes or clear time savings. For practitioners, that pattern implies pilot programs that target verifiable utility metrics tend to produce clearer business cases than broad discovery experiments.

What observers should monitor: A/B tests showing conversion lift from AI size and fit recommendations, privacy disclosures and consent rates for personalization, customer support volumes after introducing AI stock-check tools, and adoption metrics among Gen Z and Millennial cohorts. Also watch whether retailers report measurable ROI from in-store AI concierges versus online chat assistants.