50% of consumers prefer brands that don’t use AI in marketing

While companies rush to integrate artificial intelligence into ads, listings, and customer messaging, consumers are beginning to respond in unexpected ways. According to Gartner research conducted on over 1,500 American consumers, half of shoppers prefer brands that do not use AI in marketing communications. This figure serves as a wake-up call for anyone building their Amazon strategy with massive and non-transparent use of artificial intelligence.

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The paradox is clear. AI is being adopted at record speed, with over 900,000 Amazon sellers already using AI-based listing tools. Yet, consumer trust in brands that use it remains fragile.

Let’s see what the data says and how sellers can navigate this tension without losing efficiency or credibility.

>>> ou can also read our article Amazon intensifies the war against fake reviews: legal actions and AI technology <<<

What the Gartner research really says

The numbers emerging from the study are more nuanced than the title might suggest, but no less concerning. The research highlights a growing distance between the adoption of AI by brands and the trust consumers place in content generated by this technology.

Below, we have summarized the main data that sellers should be aware of:

• 50% of consumers prefer brands that do not use AI in messages, ads, and content
• 61% regularly question the reliability of the information on which they base their purchasing decisions
• 68% often doubt that the content they see is authentic, meaning real and not automatically generated
• 27% rely on intuition to distinguish reliable content from unreliable content

The picture that emerges is quite clear. Specifically, that of a consumer increasingly wary of automated content who has developed a kind of “AI fatigue.” That is, the feeling that behind perfect images, elaborate descriptions, and immediate answers, there is not a real person, but an algorithm optimizing for conversion rather than for the truth.

Why this directly impacts Amazon sellers

On Amazon, where the product detail page is the main point of contact between brand and buyer, the quality and perceived authenticity of content carry enormous weight. Titles, bullet points, descriptions, images, and reviews are the only elements on which a customer can base their purchase decision before physically receiving the product.

If consumers are already inclined to doubt AI-generated content, a listing that clearly looks “written by a bot,” with standardized phrases, generic feature lists, and an impersonal tone, risks fueling that distrust. The cost, of course, is not just aesthetic. It translates into:

• a lower conversion rate
• more pre-purchase questions
• more returns from customers who did not feel adequately informed.

At the same time, completely ignoring AI is not a viable solution. Competitors who use it intelligently:

• optimize faster
• produce content at scale
• iterate more quickly.

In short, the challenge is not choosing between AI and authenticity. Rather, it is finding a way to use it without it being seen, or better, without it being disruptive.

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Transparency and control: the two levers to regain trust

The research does not stop at photographing the problem: it also suggests countermeasures. According to the experts cited in the study, brands that manage to maintain consumer trust while using AI share some precise characteristics.

The first is transparency. Openly declaring when and how AI is involved in content creation or communication management. And this applies especially to:

• automated review responses
• post-purchase messages
• automatically generated FAQs.

A consumer who knows they are interacting with an automatic system and has the option to choose otherwise is much less distrustful than one who discovers it on their own.

The second is control. It is better to let the consumer choose whether or not to interact with AI-based features. In the Amazon context, this could translate, for example, into not forcing automated chat experiences in post-sales, or ensuring that answers to customer questions are supervised by a real person before being published.

The third, perhaps the most relevant for sellers, is verification. Namely, supporting every claim with concrete and verifiable evidence. If your product is truly the best-seller in its category, show it with data. If reviews are authentic, highlight the most detailed and specific ones. In a context where 68% of consumers doubt the authenticity of content, verifiable social proof becomes a top-tier competitive asset.

>>> Read also our article Returns on Amazon are increasing: what can we do? <<<

How to apply these insights to your Amazon strategy

Translating research results into concrete actions for an Amazon seller requires a change of perspective. AI should certainly not be abandoned, but it must be used where it adds real value without being perceived as a substitute for human experience.

Here are some practical indications we want to share with our users:

• Use AI for research, not just for writing. Keyword research tools, competitor analysis, and AI-based pricing optimization are invisible to the final consumer and highly effective. In fact, this is the area where AI adds the most value with the least reputational risk.
• Review AI-generated content with a human eye. A listing written entirely by an automatic generator without editorial review is recognizable. And consumers know how to do it! Use AI as a starting point, then customize with specific details of the product, your brand, and your typical customer.
• Prioritize detailed and specific reviews. Authentic reviews, with concrete usage details and real photos, are the most credible form of content on Amazon. Encourage satisfied customers to leave specific rather than generic feedback.
• Do not automate responses to negative reviews. A human, empathetic, and decisive response to a negative review is worth much more than a standardized automatic response. It is one of the few moments where the human presence behind the brand makes a real perceived difference.
• Monitor conversion metrics per ASIN. If a listing has undergone major AI-generated changes and conversions drop, it could be a sign that the content has lost that specificity that made it effective. Data tells you what really works.

The risk of over-relying on AI in Amazon advertising

A particularly delicate area is that of advertising campaigns. Amazon itself is integrating generative AI tools for creating images and copy in Sponsored Brands ads and video campaigns. The temptation to completely delegate creativity to these tools is strong, especially for sellers with limited resources.

But the Gartner research data invites caution. An advertising image clearly generated by AI, with that artificial perfection that many consumers now recognize, can trigger that latent distrust that leads to not clicking, or worse, to developing a negative association with the brand.

Advertising on Amazon works when the click leads to a product detail page that keeps the promises made in the ad. If the entire chain, from the ad to the listing to the reviews, appears automatically generated, the consumer perceives a distance that rarely translates into purchase and trust.

>>> Read also our article What is ROI and how is it calculated? <<<

Our opinion

The Gartner research reminds us that technology does not replace the relationship between brand and consumer: at most, it mediates it. And when that mediation becomes too evident, too cold, or too automated, the consumer withdraws.

For Amazon sellers, this does not mean going back to writing every listing by hand or responding to every review personally. It means using AI strategically, in processes where it is invisible and powerful, and preserving the human presence in moments where it truly counts: the content that convinces, the response that reassures, the brand that tells its story authentically.

Those who manage to balance technological efficiency and perceived authenticity will have a growing competitive advantage in a marketplace where everyone uses the same tools, but not everyone knows how to use them well. Having clear data on what works and what doesn’t is the first step to making decisions with awareness. And that is exactly what ZonWizard helps you do!