Retailers have committed $18.4 billion to AI-driven personalisation tools, yet a significant portion of the consumers those tools target have turned hostile. The Customertimes survey, drawn from 2,000 respondents, finds the market roughly split. Some 47 percent say they would tolerate AI in the shopping experience — but only if it actually works accurately. A further 63 percent said they would trade personal data for genuine value, though 43 percent of those attach conditions to what data they will share and in what context.
The spending has not been wasted uniformly. Recommendation engines and loyalty systems that deliver accurate, low-friction results retain consumer goodwill. The problem is pricing. Some 71 percent of respondents said AI-driven personalised pricing makes them prefer shopping in-store instead — a dynamic that now has a name in retail circles: surveillance pricing.
Two high-profile pullbacks have sharpened the industry conversation. Both Valentino and McDonald's withdrew AI marketing campaigns following customer complaints, in moves that Customertimes describes as representative of a wider trend rather than isolated brand failures.
Ken Tantsura, VP of Innovations at Customertimes, who has overseen AI deployments for Coca-Cola and L'Oréal, has been briefing media on the findings. The data suggests the enterprise AI investment case in retail depends heavily on implementation specificity: recommendation and inventory systems face less resistance than dynamic pricing and behavioural targeting, which are where consumer trust is most brittle.
For enterprise technology teams deploying AI on the customer-facing side, the Customertimes numbers reinforce a distinction that has been visible in practitioner communities for some time — optimising supply chains and logistics with AI reads differently to consumers than inferring their willingness to pay.
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