A recent US survey shows that most shoppers do not fully trust AI-based product recommendations, yet many rely on them when making purchases—and a notable share later regret those purchases.
Survey data
The study by SmartCustomer, conducted with nearly 1,200 U.S. consumers, found:
- 89% of respondents do not fully trust AI-based product recommendations.
- Nevertheless, 76% used an AI recommendation service in the past year when shopping.
- About one-third of respondents reported buying a product based on an AI recommendation that they later regretted.
Among the regretted purchases, roughly half were electronics and 45% were clothing or footwear.
Distrust and its causes
Fifty-three percent of respondents suspect that companies intentionally feed misleading information into AI systems to influence recommendations. Moreover, 98% believe AI service providers should be at least partly responsible for verifying the sources behind recommendations; the same proportion expects AI to check a business’s credibility before recommending it.
Differences by gender and generation
The survey revealed variations by gender and age cohort:
- 63% of men use AI for shopping at least occasionally, compared with 53% of women.
- 21% of Generation Z say they will never use AI for purchases, compared with 19% of Generation X and 10% of Millennials (Generation Y).
Corroborating studies and implications
Other recent research aligns with these findings:
- An RTB House marketing survey found that 35% of respondents want a human to review transactions before an AI agent finalizes a purchase; among baby boomers this rises to 44%.
- A Gartner survey published this March, with 1,500 respondents, reported that half of U.S. consumers prefer brands that do not use AI in their customer-facing messages, content, and ads, and more than two-thirds question the authenticity of the content shown to them.
Together, these results indicate that while consumers often use AI recommendations for convenience or availability, there is growing demand for transparency, source verification, and human oversight. Distrust and the rate of regretted purchases raise both commercial and regulatory questions for the design and operation of AI-based recommendation systems.
Sources and editorial note
The article references surveys by SmartCustomer, RTB House, and Gartner. It also notes that the cover image was generated with artificial intelligence. Portfolio indicates that an AI assistant helped prepare this story, and that a human journalist edited and verified the final content.
Tags: shopping, survey, consumer, artificial intelligence, baby boomer, Generation Z, recommendation, trust, consumer habits, AI
