Consumer Trust in AI Plummets Below 40% but Shoppers Still Turn to Generative AI for Product Advice

Consumer Trust in AI Hits Record Low While Usage Climbs

A paradox is unfolding in consumer behavior. Trust in generative AI has fallen below 40%, yet shoppers are turning to AI for product advice more than ever before, according to new research from 1

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. This contradiction presents immediate challenges for brands trying to influence purchase decisions through AI-driven digital platforms.

"We found significant skepticism around algorithm-driven channels like social media, and in particular generative AI, where the trust level is below 40 per cent," said Danielle Bozarth, global leader of McKinsey's Retail and Consumer Packaged Goods Practices, on 1

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. Despite this skepticism, consumers continue expanding their use of these channels for product research and evaluation.

AI Recommendations Face Credibility Crisis Across Demographics

The distrust extends beyond AI recommendations to traditional sources. Among Generation Z shoppers, even recommendations from family and friends scored surprisingly low in the research. "While these consumers are bringing more sources of information into their consideration set, they trust those sources significantly less," 1

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. This creates friction for brands and influencers attempting to shape the consumer decision journey.

Younger consumers demonstrate particularly low trust across both online and offline channels. The data reveals a generation navigating shopping advice with heightened skepticism, questioning sources that previous generations relied upon without hesitation.

Brand-Owned Websites Supply Just 1% of AI Citations

McKinsey's analysis of 25 brands over six months examined 2.6 million citations used by large language models. The findings are stark: brand-owned websites accounted for approximately 2

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. This minimal representation means companies have limited control over how product details appear in AI responses.

Large language models gather material from reviews, online communities, and third-party websites rather than official brand sources. This shift forces businesses to rethink how they structure and distribute product information across the digital ecosystem. When AI for product advice pulls from scattered sources, inconsistent or outdated details can reach consumers before verified information does.

Generative Engine Optimization Emerges as Critical Strategy

Companies are now testing generative engine optimization, commonly called GEO, to help AI systems accurately interpret their offerings. This approach involves structuring product pages with clear specifications, organized lists, and frequently asked questions that algorithms can parse effectively. GEO extends traditional search optimization into tools that answer shoppers directly through conversational interfaces.

"That creates a real challenge for brands and influencers as they try to shape the consumer decision journey," 1

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. Businesses must ensure product claims remain consistent across platforms and make verified product details easily discoverable for AI systems. Without this optimization, brands risk losing control over their narrative in AI-generated shopping advice.

Four Forces Reshaping Purchase Decisions

The research identifies four central consumer trends redefining how people shop: a technology-led path to purchase, a broader health revolution, an expanding experience economy, and the rise of the resourceful consumer. Each trend alters how shoppers compare price, quality, and usefulness.

Clarisse Magnin, Senior Partner at McKinsey, observed that consumers now evaluate products beyond upfront prices. "Resourceful is exactly the right word because consumers are becoming increasingly creative when it comes to getting greater value for their money," 1

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. Shoppers assess durability, usefulness, repairability, and resale value before committing to purchases.

Value Must Be Designed In, Not Added Later

This resourceful consumer behavior demands fundamental changes in product development. "For executives, that means value needs to be designed into the offering from the beginning, not simply added later through promotions," 1

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. Brands can no longer rely on discounts to compensate for perceived weaknesses in quality or longevity.

Consumer adoption of generative AI tools remains strongest in high-consideration purchases such as travel, beauty, and fashion. These categories involve complex decisions where shoppers seek detailed comparisons and personalized recommendations. The pressure on businesses to adjust operational and marketing strategies rapidly is intensifying as AI's role in shaping consumer behavior expands.

What Brands Should Watch For

The gap between consumer trust in AI and actual usage suggests an unstable equilibrium. Shoppers may be using generative AI out of convenience or lack of better alternatives rather than confidence in its accuracy. If AI recommendations lead to poor purchase decisions, usage could decline sharply. Conversely, improved accuracy and transparency could rebuild trust and accelerate adoption.

Brands must monitor how LLMs represent their products and actively work to supply authoritative information that AI systems can reference. Companies that master generative engine optimization early will maintain better control over their product narratives as AI-driven digital platforms become the primary research channel for more consumer segments.