Meta introduced Muse this fall as a "secure, private personal AI agent" capable of filling out forms, negotiating on users' behalf, and checking out using a digital wallet. However, major retailers are divided on the technology. Amazon blocked Muse entirely, citing concerns that the agent never identified itself when accessing the store and appeared to capture customer credentials without retailer knowledge (Retail TouchPoints). Shopify, by contrast, welcomed Muse and allows merchants to let the agent shop their stores directly. According to Bain & Company and CI&T analysts, Amazon's position reflects its dominance—holding 45%-plus U.S. ecommerce share and serving as the starting point for most ecommerce searches—and its desire to protect its data advantage and customer relationships from third-party agents (Retail TouchPoints).
Consumer readiness for agentic commerce lags behind the technology. While 74% of shoppers have used an AI tool like ChatGPT, Google Gemini, or Perplexity while browsing, and 90% have either tried one or are open to it, only 27% are comfortable letting an AI agent handle their full shopping journey (Retail TouchPoints). Trust drops sharply once financial information is at stake. Bain's research shows net trust runs negative 16% on data privacy and negative 29% on giving an agent full authority to act without step-by-step approval, with overall trust in AI slipping since last fall (Retail TouchPoints). Surprisingly, Millennials—not Gen Z—show the highest adoption rates for AI agents in retail, followed by Gen X and Gen Z (Retail TouchPoints).
Retailers best positioned for an agentic future are those with a clear, defensible value proposition on at least one purchase criterion—such as lowest price, unique selection, best service, or fastest delivery. Being second or third on every key purchase criterion puts retailers at risk of being squeezed out as AI agents optimize for what shoppers want most (Retail TouchPoints). Success will depend on retailers optimizing product discoverability through improved descriptions and strategic placement in the sources LLMs pull from, while balancing the need to remain discoverable on third-party agents with reasons for customers to visit their own sites and apps directly.