If an AI agent scours the internet for the lowest price, won’t consumers simply buy whatever the algorithm suggests? According to two reports released in 2026, the answer is no.
While AI shopping behavior is rapidly changing how consumers discover products, new research shows that the final purchase decision remains deeply human.
Generative AI is doing the heavy lifting of research, but traditional ecommerce brand trust and social proof are what actually close the sale. For sales and marketing leaders navigating the rise of agentic commerce, the data reveals a critical insight: you’ll need to do more than just optimize your product for the algorithm.
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AI is the Researcher, Not the Buyer
The adoption of AI in the retail journey has moved past early experimentation and into everyday utility.
According to a January 2026 report by Omnisend polling 4,000 consumers, 63% of Americans have used generative AI for shopping-related tasks in the past six months. However, they are not using it to blindly make purchases.
The vast majority use AI for highly practical, top-of-funnel tasks: researching and comparing products (47%), finding deals (41%), and summarizing reviews (39%).
This data is corroborated by new research from PSE Consulting, which surveyed 4,250 consumers across the US and Europe. The PSE report found that price comparison is the single most influential factor in AI-assisted shopping, cited by 32% of consumers as their primary decision driver.
What is most telling, however, is what consumers aren’t doing. Only 14% of shoppers say they simply follow the AI’s top recommendation.
Why Brand Recognition Closes the Sale
If consumers are not just clicking “buy” on the AI’s first suggestion, how are they making their decisions? The PSE Consulting research provides a stark reality check for marketers: 89% of respondents say recognizing the seller’s brand is “important” or “very important” when acting on an AI recommendation. Furthermore, 92% say customer reviews matter when deciding between AI-generated options.
“What the research shows clearly is that consumers are using agents to find the best online deals,” notes Chris Jones, Managing Director at PSE Consulting. However, he highlights there is also more to it:
“…once the shortlist is in front of the consumer, the same signals that have always driven purchasing decisions take over: does the consumer recognize the seller’s brand, and what do other customers say about it?”
This dynamic fundamentally changes how brands must approach agentic commerce. There is currently a rush to master “Answer Engine Optimization” (AEO) – ensuring your product is the one the AI selects. But being selected by the AI is only half the battle.
If an AI presents a consumer with three options, and one is a recognized brand while the other two are unknown entities, research points to the recognized brand having a big advantage. The AI may level the playing field for discovery, but ecommerce brand trust remains a core conversion metric.
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The Boundaries of Consumer Trust
While brand recognition drives the final purchase, marketers must also understand where consumers draw the line with AI autonomy. The Omnisend report highlights that while 80% of Americans are comfortable handing over transactions to AI in some form, that comfort is highly conditional.
Control and transparency are non-negotiable. Over a third of Americans (34%) are concerned about AI completing a purchase without their explicit approval.
Furthermore, the data reveals a massive red line regarding dynamic pricing. If a retailer uses AI to charge different customers different prices for the same product, 70% of Americans say they would reduce engagement, stop shopping there entirely, or leave negative reviews.
This data proves that while AI shopping behavior is accelerating – with 38% of Americans reporting they have completed a purchase directly inside ChatGPT’s new Instant Checkout feature – the underlying consumer psychology has not changed. Shoppers demand transparency. They want to know what data is being used, they want to see human reviews, and they want to click the final “buy” button themselves.
Final Takeaway
The rise of AI in shopping is not the end of brand marketing; it is a mandate to double down on it.
As AI agents take over the mechanics of search, comparison, and shortlisting, the value of a strong, recognizable brand actually increases.
The data suggests marketers may struggle if they rely solely on algorithmic optimization to drive revenue. To succeed in the era of agentic commerce, brands must ensure that when the AI presents its shortlist, the consumer sees a name they already know and trust.
FAQs
What is agentic commerce?
Agentic commerce refers to the use of artificial intelligence agents to assist with or autonomously execute online shopping tasks, such as researching products, comparing prices, or completing transactions on behalf of a consumer.
How is AI shopping behavior changing retail?
Modern AI shopping behavior shows consumers using generative AI primarily for top-of-funnel research, deal-finding, and review summarization. While AI handles the discovery phase, consumers still rely on traditional trust signals to make the final purchase.
Why is ecommerce brand trust still important with AI?
Even when an AI recommends a product, 89% of consumers say recognizing the seller’s brand is critical to their decision. Ecommerce brand trust acts as the final validation step; consumers rarely buy from unknown merchants, regardless of the algorithm’s suggestion.
Are consumers letting AI make purchases for them?
While many consumers are comfortable with AI assisting in the checkout process, the vast majority demand final approval. Only a small minority (around 16%) are willing to let AI automatically reorder products without human review.
What is the biggest consumer concern with AI shopping?
Consumers are highly concerned about data privacy, lack of control over final purchases, and AI-driven personalized pricing. A significant majority state they would abandon a retailer if they discovered AI was being used to charge different prices to different customers.
