How AI Is Changing Search Behaviors

Generative AI (genAI) is reshaping how people search for information. Anyone watching their content pageviews decline is currently experiencing the impact of this. But what’s behind the shift? The speed of the change is impressive, considering how deeply ingrained information-seeking habits can be.

In a recent qualitative study, we asked people to bring their own research tasks into the virtual lab. We explored how users' information-seeking behaviors are shifting in response to AI-powered search tools and chatbots. While AI offers compelling shortcuts around tedious research tasks, it isn’t close to completely replacing traditional search. But, even when people are using traditional search, the AI-generated overview that now tops almost all search-results pages steals a significant amount of attention and often shortcuts the need to visit the actual pages.

In This Article:

• Search Habits Are Hard to Break
• AI Changes Information-Seeking Habits
• AI Doesn’t Eliminate the Need for Search
• Gemini and ChatGPT Have a Competitive Advantage: Familiarity
• The Changing Landscape of Information Seeking
• Next in This Series
• About the Study

Search Habits Are Hard to Break

Information-seeking habits are sticky. Once someone finds a reliable way to easily find information they need, that method becomes nearly instinctive.

This partly explains Google’s massive share of the search-engine market. Over the years, many participants have told us they’ve never even considered Bing or other alternatives, simply because they’re familiar with Google and know it works well (enough) for them. In our study, multiple participants commented on their tendency to lean on what they’re already comfortable with.

“I always start with Google. It’s familiar. It’s what’s there. It’s what I’ve been doing for a long time.”
“It’s always Google for me. It’s where I always start; my search engine of choice.”
People tend to reach for whatever information-seeking tool is most convenient. One participant reflected that he got into the habit of using Google because it was built into his Chrome browser.
“At some point, I used the Google Chrome browser. It has a default setting that redirects me to Google. So, by default, I just start from google.com. I think that's the main reason I’ve stuck with this for a very long time.”

Beyond the choice of where to search for information, these habits also influence how users search. For example, several participants in our study (and many participants in other studies over the years) told us that they always skip over sponsored results on a search-results page. Some participants thought that they’re “supposed” to search this way (an example of a technology myth). Others were unable to explain why they skip the ads.

“I don’t know why I always skip the first results. Anything that says sponsored… I just tend to go to one of the top results that isn’t sponsored.”

These are information-seeking strategies that people developed over many years. It makes sense that users would fall into these habits over time, because (in most cases) they aren’t thinking much about the systems they’ll use — they’re focused on finding answers to their questions.

Users rely on them because they’ve generally worked well in the past. To change these habits, people need a significant incentive.

AI Changes Information-Seeking Habits

Generative AI’s value in information seeking is powerful enough to change those ingrained habits. Several participants were aware that their own information-seeking behaviors had started to shift since they began experimenting with AI tools.

“Oh, I always start from Google. I never use different search engines, but these days I also incorporate ChatGPT.”

Generative AI offers substantial shortcuts around the often tedious and time-consuming work required to research a topic, including:

• Defining and articulating the information need
• Overcoming information gaps and keyword-foraging problems
• Weighing and selecting credible sources
• Sifting through enormous amounts of information
• Scanning through long pages of text
• Comparing contradicting perspectives from different sources
• Synthesizing and storing information (mentally or in a note)

Even when participants utilized only a handful of genAI’s possible information-seeking benefits, they valued the assistance immensely.

AI Overviews: The First Point of Contact for Novice AI Users

Every single participant in our study had at least heard of AI and had encountered and used AI overviews on Google’s search-results pages. But a few of our participants had very limited experience with generative AI beyond those instances.

AI overviews appear at the top of results pages for many queries on web search engines. They’re powered by LLMs and attempt to quickly define keywords or answer questions.

AI overviews are the modern, upgraded iteration of the featured snippets and answer boxes introduced by Google and its competitors in the 2010s. Even then, many content sites started to notice a dent in their web traffic as people started to find answers without a click. AI overviews are even more likely to satisfy information needs without clicks.

(This feature presents a serious challenge for all content producers — NN/G included.)

A recent quantitative study by Pew Research analyzed this effect — they found that Google searchers who encountered an AI overview were substantially less likely to click on results links.

GenAI Quickly Impresses New Users

But AI overviews are limited in their usefulness — they’re better for quick definitions and fast facts (sometimes incorrect facts) than for complex information-seeking needs that involve synthesis. In these situations, AI chatbots (ChatGPT, Gemini, Google AI Mode, Perplexity, etc.) were more useful. But that use case for AI isn’t obvious to everyone.

Our study included a few participants who experienced AI chat’s info-seeking benefits for the first time during our study sessions. We watched as their information-seeking habits shifted in front of us.

For example, one participant had read AI overviews on Google and frequently used ChatGPT to write and edit emails for work but had never considered using it for information seeking until our study.

When shopping for a football (soccer to the Americans) goal for his 11-year-old son, he used Google search to find the dimensions. An AI overview helpfully supplied them.

The participant found the AI overview useful, but his utilization of AI ended there. He proceeded with his task the “old-fashioned” way — manually searching, visiting websites, and scanning web pages. When considering each option, he wanted a recognizable brand and lightweight-yet-durable construction in the correct size and in his price range. He read customer reviews and flipped through product photos. Whenever he found an option he liked, he wrote it down on a physical sticky note. The process took him 10 minutes and would probably have gone on longer if our facilitator hadn’t ended the task early for followup questions.

For a later task (diagnosing a plumbing problem in his house), we directed the participant to Gemini. It was his first encounter with Gemini, and his first time using an AI chat for information seeking. He struggled at first to communicate his precise problem but eventually was happy with the guidance it provided.

“It feels like it saved me a bit of time. It’s drawn in a lot of data and kind of tailored it to what my specific need is. [...] There’s a lot of information out there. Plumbing is a common problem. So, there’s a lot of information to sift through to get to the very specific problem I have. I think it’s done a good job.”

He recognized that he still had to communicate his need and evaluate the information it provided but was still impressed with how much time it saved him. He told us he planned to try Gemini again for more information-seeking tasks and wished he’d used it for his shopping task.

“I'll definitely use this in [the] future. I realize maybe I should have come to Gemini looking for the goals. In fact, I might do this when I get off the line and see what it says about the best places to buy regulation goals in the UK.”

This is representative of a consistent theme we observed during the study: participants (especially those with limited previous experience) were excited when they realized they could use genAI for information seeking and planned to try it out more in the future. One of our least-tech-savvy participants asked the facilitator for help bookmarking Perplexity so she could return to it later.

AI Doesn’t Eliminate the Need for Search

While generative AI does offer enough value to change user behaviors, it has not replaced traditional search entirely. Traditional search and AI chats were often used in tandem to explore the same topic and were sometimes used to fact-check each other.

All our participants engaged in traditional search (using keywords, evaluating results pages, visiting content pages, etc.) multiple times in the study. Nobody relied entirely on genAI’s responses (in chat or in an AI overview) for all their information-seeking needs.

This was true even of our participants who were highly skilled and experienced in using AI for info seeking.

Gemini and ChatGPT Have a Competitive Advantage: Familiarity

The participants in our study who were already using AI for information seeking reported being most familiar with ChatGPT and Gemini. In the habit-driven market of information seeking, this familiarity is a huge competitive advantage. In this and previous studies on AI usage, some participants were calling ChatGPT simply “Chat,” which is reminiscent of how Google became a verb (“to search” was “to google” regardless of the search engine). Linguistic shifts can portend behavioral shifts.

ChatGPT was the first modern LLM chat on the scene. It captured public attention and currently dominates the AI-chat market. But Gemini’s association and integration with traditional Google search gives it a solid chance to catch up.

One of the participants who was among the most experienced with AI explained to us why he relied on Gemini, despite having tried out ChatGPT, Grok, and Copilot.

“When people think of AI, the one they talk about most is ChatGPT. [...] I heard about ChatGPT, tried it out, and was impressed. But then I heard about similar platforms from different companies. I already use Google for a lot of things, so I started doing things on Bard. Then that turned into Gemini. Sure, there are other ones, but I just continued to use this one because it’s what I’ve used for a long time.”

These early days will be critical in the AI wars. Companies have a lot to gain from becoming users’ habitual go-to for information seeking.

The Changing Landscape of Information Seeking

Generative AI tools are undeniably useful for information seeking, and even novice users recognize that potential value right away. However, this study reminds us that, while people working in tech may feel that genAI’s uses are obvious, that is not the case for many consumers.

Even with the significant value offered by genAI, those tools are up against years or even decades of ingrained behavior patterns. The fact that some of our participants had not previously considered using genAI chat for information seeking suggests that widespread adoption will be slower than genAI fans claim. It will take even longer for the average user to utilize AI to its full potential.

Discoverability remains a major challenge for genAI design — not only the discoverability of the tools, but also the discoverability of its possible functions and how to use it.

Next in This Series

In the following articles in this series, we’ll explore themes and open questions raised by this study, including:

• The very limited AI literacy of consumers (in terms of what AI can do, how it works, and how to use it)
• When users tend to turn to genAI instead of traditional search, and how they use both in tandem
• Formation of new mental models and trust issues with AI
• Usability issues of “hybrid” search-with-AI interfaces, like Google’s AI Mode and Perplexity
• How genAI helps address the problems of knowledge gaps and keyword foraging

About the Study

We conducted remote usability testing with 9 participants from North America and the UK. We recruited for an even mix of demographic and socioeconomic backgrounds and previous AI experience levels. None of our participants worked in design or technology.

Our study was open-ended and exploratory, focusing on how users’ information-seeking behaviors have shifted in response to genAI chats and increased AI integration into global search engines, particularly Google. To encourage natural behavior, we asked participants to save anything they wanted to research using the internet for the session.

We were careful not to prime participants. Especially at the beginning of each session, we avoided telling them the study was about AI, asking them about AI at the beginning of the session, or encouraging them to use AI as participants began their research. We encouraged participants to behave however they usually would, use any site or app they liked, and spend as long as they wanted with it. 

Participants planned travel, looked for restaurants, learned about DIY projects, researched the American Civil War, studied brain microstructures, and more. Some participants had substantial prior experience using genAI tools and chose to use them. Other participants had very limited prior experience with genAI and chose traditional search methods instead. Those participants were eventually directed them to an AI tool so we could gather their first impressions (after documenting that it wasn’t their natural inclination).