Major Tech Push Meets Consumer Hesitancy as 72% Reject AI for Holiday Shopping

Major technology firms have spent the past year rolling out advanced artificial intelligence shopping tools, with Adobe projecting a 130% surge in traffic from AI assistants to U.S. retail sites this holiday season. Innovations like Google's AI shopping cart, Meta’s Muse, and OpenAI’s ChatGPT Wallet aim to streamline the retail experience and handle transactions on behalf of users. However, a recent Bank of America survey reveals a sharp disconnect between corporate ambition and consumer interest, showing that 72% of Americans do not intend to use AI for holiday gift shopping—up significantly from 49% in 2025.

According to the survey, shoppers are largely resisting AI for holiday gifts because the technology strips away the personal nature of gift-giving. Among respondents avoiding AI, 42% cited personal or ethical reasons, 37% felt it removes the personal touch from presents, and 26% expressed a lack of trust in AI recommendations. Experts note that gift-giving relies on psychological ownership, where the time and effort spent browsing and selecting an item make the gesture meaningful. Lora Monfared, head of consumer credit card products at Bank of America, noted that everyday consumers are growing more selective and experiencing bot fatigue as they monitor their budgets closely.

Consumers might just decide that it is worth it to give up a little bit of ownership of the process if it saves time, but gift giving remains deeply personal.

While holiday gifts remain a stronghold for traditional shopping, consumers are willing to delegate mundane tasks to automated systems. The Bank of America data shows that 17% of shoppers plan to use AI for comparing prices or deals, 14% for finding gift inspiration, and 7% for writing greeting cards. Marketing experts suggest that AI tools may find more enduring success in routine, impersonal chores like tracking coupons or purchasing household goods rather than managing meaningful human exchanges.

What to watch next: Monitor late-season retail data and actual transaction metrics to see if last-minute shopping scrambles force a shift away from stated consumer intentions.