AI shopping assistant usage measures how consumers use generative AI tools, chat interfaces and guided assistants to research products, compare options, get recommendations, find deals and make purchase decisions.
This page is part of the AI Commerce Statistics silo and the broader E-commerce Statistics hub. It focuses on consumer usage of AI shopping assistants in e-commerce, including research tasks, recommendation behavior, deal discovery, purchase confidence, category differences and adoption barriers.
AI shopping assistant usage: quick answer
AI shopping assistant usage is moving from novelty to practical research behavior. Adobe reported that 39% of surveyed U.S. consumers had used generative AI for online shopping in its March 2025 analysis, while its later July 2025 update reported 38% usage and 52% planning to use it during the year.
Used GenAI for online shopping
Adobe’s March 2025 consumer survey found that 39% of U.S. consumers had used generative AI for online shopping.
Planned to use it
In the same Adobe survey, 53% said they planned to use generative AI for online shopping during the year.
Used AI for research
Among AI shopping users in Adobe’s March 2025 data, product research was the most common shopping task.
Used AI for recommendations
Adobe reported that 47% of AI shopping users used generative AI to receive product recommendations.
Key AI shopping assistant usage statistics
The strongest public benchmarks currently come from consumer surveys and retail traffic analysis, so the numbers should be read as usage and intent signals.
| Statistic | What it measures | Source context |
|---|---|---|
| 39% of U.S. consumers had used generative AI for online shopping | Consumer adoption of AI-assisted online shopping | Adobe March 2025 survey of 5,000 U.S. consumers |
| 53% planned to use generative AI for online shopping during the year | Future consumer intent | Adobe March 2025 survey |
| 38% had used generative AI for online shopping | Later Adobe usage benchmark | Adobe August 2025 update |
| 52% planned to use generative AI for online shopping during the year | Future intent in Adobe’s later update | Adobe August 2025 update |
| 92% of AI shopping users said it enhanced their experience | Perceived value among people who had used AI for shopping | Adobe March 2025 analysis |
| 87% of AI shopping users were more likely to use AI for larger or more complex purchases | Usefulness for high-consideration purchases | Adobe March 2025 analysis |
What shoppers use AI assistants for
AI shopping usage is concentrated in tasks that happen before the user reaches the cart: research, narrowing choices, finding deals and understanding product options.
| Shopping task | Adobe March 2025 benchmark | Adobe August 2025 benchmark |
|---|---|---|
| Conducting research | 55% of AI shopping users | 53% of AI shopping users |
| Receiving product recommendations | 47% | 40% |
| Seeking deals | 43% | 36% |
| Getting present or gift ideas | 35% | 30% |
| Finding unique products | 35% | 29% |
| Creating shopping lists | 33% | 30% |
| Virtual try-on | Not highlighted in March 2025 list | 26% |
Practical e-commerce use cases for AI shopping assistants
For merchants, the most useful AI assistant use cases are usually tied to reducing uncertainty and helping shoppers choose between alternatives.
Product shortlist building
Assistants can help shoppers identify a smaller set of relevant products from a large catalog or market.
Feature and specification comparison
AI is useful when shoppers need to compare product attributes, compatibility, sizes, materials or technical specifications.
Price and promotion discovery
AI assistants can guide deal-seeking behavior, which affects how merchants present offers, bundles and discounts.
Purchase confidence support
Assistants can answer questions that otherwise lead to abandonment, support tickets or delayed purchase decisions.
Trust and adoption barriers
Even when shoppers use AI assistants, they may not trust every answer. E-commerce teams should treat assistant output quality, data accuracy and transparency as conversion factors.
| Barrier | Why it matters | What merchants can improve |
|---|---|---|
| Wrong or incomplete product facts | Bad recommendations reduce trust and can create returns or support issues. | Keep product data structured, complete and crawlable. |
| Unclear source of recommendation | Shoppers may not know why an assistant suggested a product. | Make specifications, reviews, availability and pricing easy to verify. |
| Privacy concerns | Personalized assistants may require behavioral or preference data. | Explain data use and avoid intrusive personalization. |
| Category fit | Some categories need visual taste, fit or human judgment. | Use AI as support, not as a replacement for useful product content. |
AI shopping assistant usage by segment
AI assistant usage is likely to vary by product complexity, customer age, device behavior and purchase risk.
| Segment | Likely behavior | Measurement idea |
|---|---|---|
| High-consideration purchases | Higher assistant usefulness because users need comparison and confidence. | Track assisted landing pages, PDP depth and repeat sessions. |
| Gift shoppers | AI can generate ideas when the buyer lacks product knowledge. | Track seasonal AI referrals and gift guide landing pages. |
| Technical categories | AI can help explain compatibility, specifications and trade-offs. | Track support questions before and after assistant-led traffic. |
| Fashion and beauty | AI can inspire, but taste, fit and image trust remain important. | Track recommendation satisfaction, returns and visual content engagement. |
| B2B buyers | Assistants can support product matching, quoting and procurement research. | Track assisted quote requests, account logins and search refinements. |
Methodology notes
AI shopping assistant usage data can describe many different behaviors, from using ChatGPT for gift ideas to using an onsite retail assistant.
| Issue | Why it matters | How to handle it |
|---|---|---|
| Offsite AI vs. onsite assistant | A consumer may use a general AI tool before visiting a merchant website. | Separate AI referral traffic from onsite assistant engagement. |
| Usage vs. trust | Using AI does not mean the shopper fully trusts the answer. | Track satisfaction, returns, support tickets and conversion outcomes. |
| Research vs. checkout | AI is often used before the purchase decision, not only during checkout. | Measure assisted discovery and consideration, not just last-click revenue. |
Cite this page
BestForEcommerce. “AI Shopping Assistant Usage.” BestForEcommerce.com, 2026. Available at: https://bestforecommerce.com/ecommerce-statistics/ai-commerce/ai-shopping-assistant-usage/