Adobe says AI travel traffic to US sites jumps 119%

Adobe has released new research on the rise of AI-referred traffic to US travel websites, which increased 119% year on year in July.

The figures point to a shift in how travellers research and book trips, with AI tools increasingly used to gather ideas, compare options and build itineraries before users click through to a travel brand's website.

The findings are based on direct online transactions covering more than 1 trillion visits to US retail sites, alongside a survey of more than 5,000 US respondents conducted in July 2026. The research focused on the travel and retail sectors, examining both traffic patterns and how readable websites are to large language models.

In travel, the main uses of AI were research and inspiration, each cited by 43% of respondents. Transportation planning followed at 41%, while 34% said they used AI for itinerary creation. Overall, 84% said using AI for travel planning improved their experience.

The data also suggests users arriving from AI tools are becoming more commercially valuable for travel companies. In July, AI conversion was 1% lower than non-AI traffic, a sharp improvement from July 2025, when conversion from AI traffic was 47% lower.

Trust appears to be part of that shift. According to the survey, 95% of respondents who use AI tools said they believe the responses are just as trustworthy as traditional search.

Behaviour on travel sites also differed from other traffic sources. Engagement rates for visitors arriving from AI sources were 21% higher than for non-AI traffic, visits were 67% longer and bounce rates were 42% lower.

Visibility gaps

Alongside the traffic growth, Adobe highlighted a separate issue for travel brands: whether AI systems can properly read and surface their content. It used its AI Content Visibility Checker to assess pages across hotels, cruise lines, car rental services and airlines.

The scoring system measures what proportion of page content is readable by machines. A score of 50% means half of a page's content is not readable to large language models.

Hotel homepages achieved an average score of 71%. Cruise line homepages scored 70%, car rental services 64% and airlines 42%, suggesting airline sites had the widest machine-readability gap among the travel categories reviewed.

Scores on product-style pages were somewhat higher. Cruise lines led with 76% for pages such as itineraries and ship options, followed by car rentals at 73%, hotels at 68% and airlines at 59% for pages such as routes and fares.

The findings indicate that visually rich design alone may not be enough if key details such as amenities, prices or availability are difficult for AI systems to interpret. For travel groups that depend on discovery through search and recommendation tools, that could affect whether they appear in AI-generated answers.

Retail comparison

The same broader pattern is visible in retail, where AI is increasingly acting as an entry point for online shoppers. AI traffic to US retail sites rose 62% year on year in July and has increased 1,219% since October 2024.

Unlike travel, AI-referred traffic in retail is already converting better than other channels. Conversion from AI sources was 60% higher than non-AI traffic in July, marking the 11th consecutive month in which AI conversion outperformed.

Retail visitors from AI sources were also more engaged. They spent 59% more time on site, were 33% less likely to bounce and added items to their carts at a 28% higher rate than visitors from non-AI channels.

Yet many US retailers also have significant visibility gaps. Average homepage visibility across a broader set of retail sites stood at 61% in July, down from 75% in an earlier April 2026 analysis, meaning nearly 40% of homepage content was not fully readable by machines.

Across retail categories, apparel scored highest for overall readability at 76%, followed by electronics at 70% and cosmetics at 68%. Sporting goods scored 67%, furniture and home 64%, general merchandise 63% and grocery 59%.

Better-performing categories tended to have more consistent and structured product content, along with stronger coverage across editorial and owned digital channels. Lower-scoring sectors may need to review how content is presented across homepages, product pages and corporate publishing if they want to improve their presence in AI-driven discovery.

The travel findings show a market where AI is moving beyond early experimentation into a booking channel that performs almost as well as established digital sources. At the same time, Adobe's data suggests many brands still face a basic problem: if large language models cannot read key parts of their sites, they may struggle to appear where customers are increasingly starting their journeys.