Generative AI traffic share measures how often retail and e-commerce visits originate from AI search systems, answer engines, AI browsers, chat interfaces and shopping assistants. The channel is still small compared with paid search, email or organic search, but it is growing quickly enough to deserve separate tracking.
This page is part of the AI Commerce Statistics silo and the broader E-commerce Statistics hub. It focuses on generative AI traffic to e-commerce and retail websites, including AI referrals, AI-assisted discovery, engagement quality, conversion gaps, device mix and measurement caveats.
Silo: AI Commerce
Primary metric: AI referral and visit share
Best used with: channel definition, attribution source and date
Generative AI traffic share: quick answer
Generative AI traffic is growing from a small base. Adobe Analytics reported a 1,300% year-over-year increase in traffic from generative AI sources to U.S. retail sites during the 2024 holiday season, a 1,200% increase in February 2025 compared with July 2024, and a 4,700% year-over-year increase in July 2025. The important context is that Adobe still describes the channel as modest compared with larger sources such as paid search or email.
Holiday 2024 YoY increase
Adobe observed a major year-over-year increase in generative AI traffic to U.S. retail sites during Nov.–Dec. 2024.
February 2025 vs. July 2024
Adobe reported that generative AI traffic to U.S. retail sites increased 1,200% in February 2025 compared with July 2024.
July 2025 YoY increase
Adobe later reported continued momentum, with generative AI traffic to U.S. retail sites up 4,700% year over year in July 2025.
Consumers using GenAI for shopping
Adobe’s July 2025 update reported that 38% of surveyed U.S. consumers had used generative AI for online shopping.
Key generative AI traffic statistics for e-commerce
These statistics should be read as directional benchmarks for AI-assisted discovery, not as universal channel shares for every store.
| Statistic | What it measures | How to use it |
|---|---|---|
| 1,300% YoY increase during the 2024 holiday shopping season | Growth in generative AI traffic to U.S. retail sites | Use as evidence that AI-assisted shopping discovery became visible during peak retail season. |
| 1,950% YoY increase on Cyber Monday 2024 | Peak-day generative AI traffic growth | Use with caution because peak days can amplify emerging channel behavior. |
| 1,200% increase in February 2025 vs. July 2024 | Post-holiday AI traffic growth trend | Use as evidence that the behavior continued beyond the holiday spike. |
| 4,700% YoY increase in July 2025 | Later Adobe update on AI traffic growth | Use as a more recent directional benchmark for AI-powered shopping momentum. |
| 38% of surveyed U.S. consumers had used generative AI for online shopping | Consumer usage of generative AI in shopping journeys | Use to connect traffic growth with shopper behavior. |
| 52% planned to use generative AI for online shopping during the year | Consumer intent to use AI for shopping | Use as future-looking context, not as measured site traffic. |
Why generative AI traffic is growing
AI-driven traffic grows when shoppers use chat interfaces or AI-powered search tools to compare products, ask questions, find deals and narrow choices before clicking through to a retailer.
Product research and comparison
Shoppers use AI tools to summarize options, understand differences and build shortlists before visiting a store.
Deal and discount discovery
AI can help shoppers look for promotions, alternatives and cheaper substitutes before they commit to a retailer.
Gift and product inspiration
Generative AI can influence early-stage discovery when the shopper does not yet know what product to buy.
Large or complex purchases
AI-assisted research is especially relevant when products require comparison, specifications or confidence-building.
Engagement quality from generative AI traffic
Early AI traffic does not always convert at the same rate as mature channels, but Adobe’s data suggests AI-referred users may arrive more informed and more engaged.
| Metric | Adobe benchmark | Interpretation |
|---|---|---|
| Engagement time | 8% higher engagement vs. non-AI traffic sources in Adobe’s March 2025 analysis | AI-referred users may be arriving after a more informed research session. |
| Pages per visit | 12% more pages per visit vs. non-AI traffic sources | AI traffic can indicate deeper comparison behavior. |
| Bounce rate | 23% lower bounce rate vs. non-AI traffic sources | AI-referred visits may be more qualified than generic discovery traffic. |
| Conversion gap | AI traffic was 9% less likely to convert in Adobe’s March 2025 analysis, improved from a larger earlier gap | AI traffic may still sit higher in the research funnel, but conversion quality can improve over time. |
| Device mix | 86% desktop share for AI traffic in Adobe’s Nov. 2024–Feb. 2025 data | AI shopping research may happen more often on desktop interfaces than normal e-commerce traffic. |
How to measure generative AI traffic share
In analytics, generative AI traffic should be separated from traditional organic search, referral traffic and direct traffic wherever possible.
Generative AI traffic share
Generative AI traffic share is the percentage of visits or sessions that can be attributed to AI search systems, chat interfaces, AI browsers or answer engines.
AI-assisted discovery
AI-assisted discovery is broader than direct referral traffic. A shopper may use an AI tool to research a product and later visit directly or through search, which makes attribution harder.
AI referral source
An AI referral source is a measurable referring domain, app, browser or platform that passes the user to the merchant website after an AI-assisted interaction.
Segments and category interpretation
AI traffic should be interpreted by product category, device, purchase complexity and region.
| Segment | Likely AI traffic pattern | What to watch |
|---|---|---|
| Electronics and complex products | Higher usefulness because shoppers compare specifications and trade-offs. | Compare AI traffic conversion to search and product detail page engagement. |
| Apparel and style-led categories | AI may help with inspiration, but fit, taste and visual trust remain barriers. | Track assisted discovery, not only direct conversion. |
| Gift categories | AI can generate ideas and shortlists before users click to stores. | Watch holiday spikes and seasonal query behavior. |
| Large retailers and marketplaces | More likely to receive early AI referrals because they have broad catalogs and strong brand recognition. | Segment by category and query type. |
| Niche stores | May benefit when content is structured and product expertise is clear. | Improve crawlability, product facts and machine-readable content. |
Related AI commerce datasets
Use these related pages to connect this benchmark with the rest of the AI Commerce silo.
AI Adoption in E-commerce
Track how merchants and retail teams are evaluating, testing and implementing AI.
AI Shopping Assistant Usage
Measure how consumers use AI tools for research, recommendations, deals and purchase support.
AI Product Recommendation Impact
Connect recommendation engagement with revenue, orders, AOV and conversion behavior.
Methodology notes
Generative AI traffic benchmarks are highly time-sensitive because the channel is emerging from a low base.
| Issue | Why it matters | How to handle it |
|---|---|---|
| Low base effect | Growth rates can look very large when the starting share is tiny. | Report both growth rate and share of total traffic when available. |
| Referral detection | AI tools do not always pass clean referral data. | Create dedicated channel rules and monitor referrers, landing pages and query patterns. |
| Research vs. purchase | AI users may research before buying later through another channel. | Interpret AI as an assisted discovery signal, not only a last-click conversion source. |
| Fast update cycle | Benchmarks can change monthly. | Use the newest source date and avoid treating older growth rates as permanent. |
Cite this page
BestForEcommerce. “Generative AI Traffic Share.” BestForEcommerce.com, 2026. Available at: https://bestforecommerce.com/ecommerce-statistics/ai-commerce/generative-ai-traffic-share/