Most web shoppers are already using AI while shopping, but many still struggle to get the outcomes they need, based on Adobe for Business research.
Adobe surveyed greater than 1,000 shoppers within the US and located that 86% use AI tools while shopping. The tools range from integrated retail features, similar to product recommendations and image search, to generative AI chatbots and customer support windows.
AI tools are common in online shopping
The survey showed that many consumers use AI tools but still struggle when requests require specific wording. Nearly one in five shoppers said that they had abandoned an AI shopping request because they didn’t know how one can phrase what they wanted.
Shoppers tried a median of three prompts before giving up on AI-generated recommendations. Among Gen Z shoppers, nearly one in 4 abandoned a request through the search process.
The research also found differences in how consumers prompt AI tools. Gen Z shoppers wrote prompts that were 25% more detailed than those written by Baby Boomers when requesting shopping recommendations.
Integrated AI tools remain more commonly used than standalone generative AI chatbots. “Recommended for you” sections and image search were each utilized by 52% of shoppers. Customer service chat windows and generative AI chatbots were each utilized by 36%.
Size and fit predictions based on past purchases were utilized by 33% of shoppers. Such tools use past purchase data and product information to generate recommendations.
Electronics and apparel lead AI-assisted shopping
AI-assisted shopping was commonest in electronics and apparel. Adobe found that 40% of shoppers used AI shopping assistance for electronics, while 39% used it for attire and accessories.
Beauty and private care followed at 32%, while health and wellness accounted for 31%. Groceries and food delivery accounted for 26%, and toys and games accounted for twenty-four%.
Among parents with children under 18, 37% used AI tools for toy and game purchases. That compares with 24% of all shoppers.
Comparison and price tracking are top use cases
Some shoppers reported savings from using AI tools. Nearly one in seven said they saved US$500 or more last yr through AI-assisted shopping.
The mostly cited advantages were faster product comparisons and time savings. Adobe found that 54% of shoppers valued AI’s ability to match products quickly, while 53% cited time savings.
Another 41% said AI gave them access to more product information. Easier product discovery was cited by 39%, while money-saving was cited by 35%.
Shoppers wanted probably the most AI assistance with research and comparison. Adobe found that 62% wanted support on this area, while 56% wanted help monitoring deals and costs.
Inspiration and discovery was cited by 33% of shoppers. Fit and validation was cited by 24%, while order management, returns, and customer support were each cited by 22%.
Shoppers want AI tools to recollect key details
The survey also showed what varieties of information shoppers wanted AI tools to recollect. Size was cited by 55%, while budget range was cited by 54%.
Purchase history followed at 53%, while style preferences were cited by 52%. Loyalty status was cited by 42%.
Life context, similar to household needs or personal circumstances, was cited by 21%.
Privacy stays the highest concern
The survey also asked shoppers about concerns around AI shopping assistants. Privacy was the highest concern, cited by 29% of shoppers.
Bias in recommendations was cited by 24%, while lack of trust was cited by 23%. Adobe also found that 75% of shoppers said AI-generated content wouldn’t deter them from making a purchase.
When asked what would increase their engagement with AI shopping tools, 39% of shoppers cited improved advice accuracy. More reliable data was cited by 33%.
Enhanced privacy controls followed at 31%. The ability to recollect past preferences was cited by 27%, while improved personalisation was cited by 26%.
Greater transparency around how AI functions work was cited by 25%.
Shoppers struggle with prompts
The research also examined how consumers describe shopping needs when using AI. When looking for a laptop, shoppers were 80% more prone to mention a budget than when shopping for a gift.
Brand names appeared more often than price limits. Adobe found that shoppers were thrice more prone to name a specific brand than to set a price cap.
Technical specifications were less common in prompts. Fewer than one in five shoppers included technical details. RAM and storage were probably the most common specifications, at 11% and 10%, respectively.
Product data shapes AI recommendations
Adobe described agentic AI in retail as systems that interpret shopper intent and take motion without requiring precise prompts. These actions can include recommending products or guiding a shopping journey.
Adobe said these systems use product data and customer history to answer incomplete shopping requests. Behavioural signals and approved content also can help shape the response.
Adobe’s research also found that 26% of shoppers recognised the advantages of brand name loyalty from AI-powered personalisation. The company said AI agents, real-time customer profiles, and product knowledge systems are used to match shopping requests with product information.
Shoppers said improved advice accuracy and more reliable data would increase their use of AI shopping tools. They also cited stronger privacy controls, memory of past preferences, and clearer explanations of how AI functions work.
(Photo by حامد طه)
See also: How AI is moving more ad production in-house
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