The AI shopping gap: Why 86% of consumers use AI but still can’t get what they need.

This post will cover:

• How AI is reshaping online shopping
• Using brand concierge agents to boost customer intent
• Turning agentic AI into smart conversations
• Streamlining the conversational path to purchase
• Bridging the gap from prompt to purchase

Key findings.

• AI assists 86% of shoppers in retail journeys.
• While 36% utilize generative AI chatbots, most rely on integrated brand tools like recommended for you sections (52%) and image search (52%).
• Nearly one in seven shoppers saved $500 or more last year using AI tools.
• Nearly one in five shoppers abandoned an AI shopping request because they don't know how to ask for what they want.
• Consumers attempt an average of three prompts to receive their desired product recommendations before giving up on AI recommendations.
• Gen Z writes 25% more detailed prompts than Baby Boomers when requesting shopping recommendations from AI.

Online shopping has always depended on knowing what to search for and how to say it. Today, 86% of shoppers use AI during their retail journeys — yet many still can't get the results they need. The barrier isn't trust. It's translation: shoppers know what they want but struggle to communicate it in a way that returns useful results. That gap between intent and outcome is exactly where conversational commerce makes its case — and where brands have the most to gain by moving beyond passive AI features toward experiences that interpret what shoppers mean, not just what they type.

According to the recent Adobe for Business research, 26% of shoppers recognize the benefits of brand loyalty from AI-powered personalization, and 75% say AI-generated content would not deter them from making a purchase.

But adoption is breaking down at the critical moment when shoppers try to translate intent into a prompt. To understand where AI shopping tools have room to improve, Adobe surveyed over 1,000 US shoppers. The findings reveal a telling gap; nearly one in five shoppers abandon AI tools not due to distrust, but because they don't know how to articulate their needs.

To close this gap, brands need systems that can reference real-time customer profiles, behavior signals, and content to make informed decisions about what customers may be looking for. Adobe Experience Platform agents address this by delivering intent-driven, personalized experiences — powered by specialized AI agents coordinated through Adobe Experience Platform Agent Orchestrator. Where shoppers struggle to articulate what they need, Brand Concierge handles the translation by referencing real-time customer profiles, behavioral signals, and brand content to determine what customers are most likely looking for — turning vague queries into relevant, connected experiences.

AI-powered conversational commerce tools are changing how shoppers discover, evaluate, and choose products. Features like "recommended for you" sections have existed for years, but generative and agentic AI now make these experiences significantly more dynamic — adapting in real time to intent, context, and behavior rather than relying on static rules or basic collaborative filtering.

Shoppers interact with AI across two main categories: native on-site features integrated directly into a brand's retail experience — such as "recommended for you" sections, image search, and automated review summaries — and external generative AI chatbots like standalone LLM tools. The study found the top ways shoppers use these tools include.

People are quickly moving beyond simple search to find what they need. 86% of shoppers are willing to use AI tools to assist them through their purchase journey. These tools are now a regular part of how people buy. In fact, two in five shoppers use AI to improve their retail experience on a weekly basis.

Shoppers interact with AI in several ways to find products and get help — ranging from passive, integrated features to active generative tools:

• 'Recommended for you' sections: 52%
• Image search: 52%
• Customer service chat windows: 36%
• Generative AI chatbots: 36%
• Size and fit predictions based on past purchases: 33%

Of these, generative AI chatbots represent the most active and conversational form of AI assistance — and the category where agentic capabilities such as intent interpretation and dynamic response generation are most common. The findings suggest a growing shopper preference for guided discovery over active prompting. Consumers increasingly want results delivered intuitively, without needing to learn or navigate the interface themselves.

AI tools don't just personalize experiences — they deliver tangible value. Nearly one in seven customers report saving $500 or more using AI during their shopping journey, reflecting greater confidence that they found the right product at the right price.

Top purchase categories from AI-assisted recommendations.

AI-assisted shopping is more common in some product categories than others. Shoppers are more likely to use an AI shopping assistant for items with clear technical specs or style trends, including:

• Electronics: 40%
• Apparel and accessories: 39%
• Beauty and personal care: 32%
• Health and wellness: 31%
• Groceries and food delivery: 26%
• Toys and games: 24%
• Books and media: 22%
• Home goods and furniture: 20%

Certain groups find even more value in these personalized product recommendations. Among parents with children under 18, AI-assisted toy and game shopping outpaces the general population, with 37% using AI tools for this category compared to 24% of all shoppers.

The value of these experiences depends on the quality of the data, content, and product context behind them. A size predictor is only useful if it can draw on relevant purchase and preference data. A "recommended for you" experience works best when it reflects more than a single session. Adobe Real-Time CDP helps unify customer data into real-time profiles, while Adobe Brand Concierge uses that context (alongside approved content, product knowledge, and conversational signals) to deliver more relevant guidance.

Together, as part of a broader Adobe experience architecture, Real-Time CDP and Brand Concierge help brands connect fragmented signals to personalized conversations. Rather than relying only on isolated clicks, brands can guide shoppers using richer profile data, behavioral context, and product information — enabling more relevant recommendations, smarter assistance, and smoother handoffs to human support when needed.

Shoppers report clear value from AI across the shopping experience, but the data reveals something more specific than general satisfaction. The biggest wins cluster around moments that are inherently conversational: comparing options, evaluating tradeoffs, and making decisions with confidence. These aren't tasks that passive, integrated features handle well on their own. They're tasks that require dialogue, which is precisely why conversational AI experiences outperform static recommendations at the moments that matter most. Understanding where shoppers feel that gap most acutely reveals where brands should focus.

Shoppers reported the top benefits of AI for online shopping as:

• Ability to compare products quickly: 54%
• Time-saving: 53%
• Access to more product information: 41%
• Easier product discovery: 39%
• Money-saving: 35%

These findings reflect something bigger than convenience. AI agents are helping people handle complex shopping journeys by organizing data and highlighting the best choices. When a brand uses an enterprise AI chatbot or Adobe Brand Concierge, they help shoppers find exactly what they need without the usual stress of endless scrolling. This shift toward conversational commerce ensures that every customer experience is fast, helpful, and tailored to each shopper's specific needs.

Adobe is building the infrastructure to make such connected experiences possible at scale. At the center is Adobe Experience Platform Agent Orchestrator, the intelligence layer that interprets customer intent and coordinates a suite of specialized AI agents, each designed to handle a distinct part of the customer journey.

Powered by Agent Orchestrator, Adobe Brand Concierge uses specialized AI agents to handle distinct parts of the customer journey — from surfacing relevant product recommendations in plain language to enabling seamless handoffs to human support when needed. The result: a single shopper interaction that moves fluidly from discovery to decision without feeling fragmented.

Where consumers most want help from agentic AI assistants in the shopping journey:

AI delivers the most value at high-effort moments, like when shoppers need to compare, evaluate, or make decisions:

• Research and comparison: 62%
• Deals and price monitoring: 56%
• Inspiration and discovery: 33%
• Fit and validation: 24%
• Order management and returns: 22%
• Customer support: 22%

These preferences reveal a consistent pattern: shoppers want AI to do the heavy cognitive lifting at the moments that matter most — research, comparison, and deal evaluation. And they're willing to share personal context to make that help more relevant. The most commonly requested memory features (size, budget, purchase history, and style preferences) map directly to the highest-friction points in the shopping journey.

What consumers want AI assistants to remember to improve shopping experiences:

Shoppers aren't just open to AI assistance — they have a specific vision for it. Demand is highest during the most strenuous parts of the shopping journey, and they're willing to share personal context to make that help feel relevant.

• Size: 55%
• Budget range: 54%
• Purchase history: 53%
• Style preferences/taste: 52%
• Loyalty status: 42%
• Life context: 21%

Despite strong adoption, trust and transparency persist as barriers. Building a strong connection with shoppers means understanding their needs and addressing their concerns. Solving these barriers is the best way to create a better customer experience.

Shoppers reported their top concerns for AI shopping assistants as:

• Privacy: 29%
• Bias in recommendations: 24%
• Lack of trust: 23%

The biggest friction point is surprisingly simple: not knowing how to ask. Nearly one in five shoppers has abandoned a request because they couldn't phrase it the right way. Adobe Brand Concierge addresses this by focusing on intent rather than perfect phrasing, making it easier to get relevant recommendations without the trial and error of traditional search.

What shoppers say would increase their AI shopping tool engagement

• Improved accuracy of recommendations: 39%
• More reliable data: 33%
• Enhanced privacy controls: 31%
• Ability to remember past preferences: 27%
• Improved personalization: 26%
• Greater transparency on how AI functionality works: 25%
• Wider range of products and services: 23%
• More human-like interaction: 18%

Consumers want personalized, efficient online shopping experiences, with the assurance of a secure data infrastructure and enterprise-grade governance to address privacy and trust concerns.

The research tells a consistent story: shoppers are willing to engage with AI, but the experience breaks down the moment they have to articulate what they want precisely. Most try an average of three prompts before giving up. Nearly one in four Gen Z shoppers abandon a request entirely despite writing more detailed prompts than any other demographic. This isn't a feature problem; it's a conversation design problem. The brands best positioned to win the next phase of digital commerce are the ones that stop waiting for shoppers to find the right words and start building experiences that meet them where their intent already is.

While many shoppers struggle with developing the perfect query, those frustrations may run deeper still. Shoppers will try an average of three prompts before giving up.

This challenge is even more pronounced for Gen Z. Nearly one in four abandon a request mid-search — even though they provide more detail than any other group.

Prompting habits also shift depending on what someone is shopping for. When searching for a laptop, shoppers are 80% more likely to mention a budget than when shopping for a gift — yet brand names consistently outweigh price. Shoppers are three times more likely to name a specific brand than to set a price cap. Technical specs, meanwhile, barely register: fewer than one in five shoppers included them, with RAM and storage the most common at 11% and 10% respectively.

The pattern is consistent: in the research phase, shoppers lead with goals, not specifications. Shoppers are eager to use AI; however, they may lack the technical specificity or persistence needed to get the best results. Adobe Brand Concierge helps bridge that gap in conversational commerce by using brand data to interpret shopper intent and deliver precise recommendations, without requiring shoppers to use technical language. Agentic AI assistance shifts the experience from a passive interface to an active guide throughout the customer journey.

The prompt gap isn’t just a challenge — it’s a competitive opportunity. Here are some strategic solutions for closing the shopping prompt gap:

• Lower the barrier to entry with guided intent. Preempt consumer frustration and purchase abandonment with guided discovery and fallback logic from Adobe Brand Concierge to suggest clarifying questions to keep the journey moving.
• Provide contextual reasoning to solve the ‘brand over budget’ approach. Automatically apply budget ranges and past purchase history to the customer journey via Adobe Brand Concierge’s agentic reasoning and Real-Time CDP insights to ensure recommendations are viable.
• Optimize for lack of shopper specificity. Ensure your products surface clearly in AI-driven experiences by structuring content for discoverability and summarizing complex specs into benefit-driven language.

The opportunity isn’t just to add AI; it’s to remove friction. Brands that can translate intent into action will win the next phase of digital commerce. By interpreting intent and guiding discovery, agentic AI can recover stalled journeys and turn hesitation into confident purchases.

The value of these experiences depends on the quality of the data, content, and product context behind them. A size predictor is only useful if it can draw on relevant purchase and preference data. A "recommended for you" experience works best when it reflects more than a single session. Adobe Real-Time CDP helps unify customer data into real-time profiles, while Adobe Brand Concierge uses that context — alongside approved content, product knowledge, and conversational signals — to deliver more relevant guidance.

Together, as part of a broader Adobe experience architecture, Real-Time CDP and Brand Concierge help connect fragmented signals to personalized conversations. Rather than relying only on isolated clicks, brands can guide shoppers using richer profile data, behavioral context, and product information — enabling more relevant recommendations, smarter assistance, and smoother handoffs to human support when needed.

See how Adobe Experience Platform and Adobe Brand Concierge help brands turn intent into action — watch the overview video.

Methodology

This article is informed by proprietary research conducted by Adobe. The study surveyed 1,000 consumers across the United States, providing a 95% confidence level with a ±3% margin of error. Respondents were asked about shopping habits utilizing AI. As with all self-reported data, results may reflect personal perceptions and experiences that could differ from actual behaviors.