Do people turn to an AI assistant before searching the web, or only after they've already started browsing?
Do assistant sessions interleave with web content differently than search sessions do?
This explores whether people weave AI assistant use into their browsing differently than they weave in search: what comes before and after each, and whether assistants replace search or sit alongside it.
This explores whether AI assistants fit into a person's web journey differently than search engines do. The question is whether people reach for assistants at a different point in their browsing, and whether assistant use replaces search or runs alongside it. The corpus says they do fit in differently, and in a direction you might not expect. A cross-surface panel study that tracked the same users across search, browsing and assistants found that search tends to open a journey toward content, while assistant sessions more often come after it. Assistant use followed earlier web activity 20.6 percentage points more often than it preceded it Do people use AI assistants before or after searching?. That undercuts the popular 'answer engine' story, where people ask a chatbot first and never visit a website. In practice, many people browse first and then bring what they found to an assistant, perhaps to digest, compare or act on it.
The same study adds a twist: within the same users, sessions that used only an assistant were more common than sessions that used only search Do people use AI assistants before or after searching?. So assistants show up in two modes. Some sessions are self-contained, with the user never leaving the chat. Others are follow-ups attached to web activity. Search mostly works as an entry point. Qualitative work fits this picture. Nielsen Norman Group found that every participant kept using traditional search throughout their tasks, often running chat and search side by side, and the main thing holding back AI use was not knowing when it would help, not distrust Does generative AI chat actually replace traditional search?.
The pattern also runs the other way: assistant-style content is moving into the search page. Eye-tracking research shows AI Overviews now take the visual 'golden triangle' that the top-ranked result used to hold. Attention to the first result fell from 31% to 9%, and trust ratings stayed equally high for both Where do searchers look when AI Overviews appear?. So the line between an 'assistant session' and a 'search session' is blurring from both directions. People carry web content into chats, and search pages put an assistant-style summary in front of the links.
Why might the order matter? An 8-day field experiment found that people who learned with ChatGPT did worse than Google searchers, especially on critical-thinking questions. The authors traced this to less agency over which sources to read and less exploration of the wider topic Does ChatGPT harm informal learning compared to Google Search?. Read alongside the sequencing data, this suggests that the common habit of browsing first and then asking the assistant may protect people. It keeps the exploring step that assistant-only sessions skip. That is an inference: none of these studies tested it directly.
A caveat: the corpus has one study that measures the interleaving directly. The others tell you what people do around it (running tools in tandem, where attention lands, what gets learned), not the fine-grained order of steps within a session. If you want the hard numbers, start with the panel study. Read the others for why the pattern might matter.
Sources 4 notes
A cross-surface panel study found assistant sessions come after search and browsing 20.6 percentage points more often than before, reversing the "answer engine" narrative. Assistant-only sessions are also more common than search-only sessions within the same users.
Nielsen Norman Group's qualitative study found all participants continued using traditional search throughout tasks, often running both methods in tandem. The main barrier to AI adoption is not resistance but lack of awareness about when and how to use AI chat for information-seeking.
Eye-tracking data shows AI Overviews receive significantly longer fixation times, reducing attention to the first-ranked result from 31% to 9%. Trust ratings between AI Overviews and ranked results remained equally high despite this attention shift.
In an 8-day field experiment, ChatGPT users scored lower on knowledge tests, especially on critical thinking items, due to reduced agency in information selection and two distortions: ChatGPT's bias toward solutions over principled knowledge, and its conversational interface reducing exploration of the broader knowledge space.
Papers this line draws on 8
The research behind the notes this line reads — ranked by how closely each paper relates.
- How AI Is Changing Search Behaviors
- The New Shape of Search: How Conversational AI Recomposes Information Seeking
- Learning by Chatting? Investigating the Impact of Generative AI on Information Seeking and Learning
- An Eye Tracking Study: Are AI Overviews Changing Search Behavior?
- Seeing to Think? How Source Transparency Design Shapes Interactive Information Seeking and Evaluation in Conversational AI
- Google users are less likely to click on links when an AI summary appears in the results
- Experimental evidence of the effects of large language models versus web search on depth of learning
- Investigating the Impacts of Generative AI on Information Seeking