GenAI for Complex Questions, Search for Critical Facts

Users choose AI to explore and synthesize information; but they rely on traditional search when accuracy and trust are critical.

GenAI for Complex Questions, Search for Critical Facts

Maria Rosala and

Josh Brown

February 27, 2026

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Summary:
Users choose AI to explore and synthesize information; but they rely on traditional search when accuracy and trust are critical.

Users are increasingly turning to generative AI (genAI) for information-seeking tasks — but not uniformly. In a recent study, we observed how people chose between AI chatbots and traditional search for real tasks. Users turned to AI when they started with vague ideas, juggled multiple requirements, or combined information from many sources. They used traditional search when they needed accuracy, control, and trusted sources.

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In This Article:

Why Users Turn to GenAI

Why Users Still Turn to Search

About the Study

Conclusion

Why Users Turn to GenAI

AI as a Starting Point when the Next Step Is Unclear

Some participants began with genAI chatbots when they weren't yet sure what they were looking for or how to describe it. Unlike traditional search tools, which require specific search keywords and, thus, some knowledge about the topic, chatbots offer greater flexibility when the search space is unfamiliar.

Participants used vague or exploratory prompts and let the AI suggest possible directions.

“It's made starting research or looking into something a little bit easier because it can kind of give you the best options to start.”

"It’s (...) one of the most helpful places to start. (...) It can really help direct me into a more narrow type of search."

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One participant, who had recently purchased a Kindle, wanted to find free books to read on it. He wasn’t sure what options existed, so he turned to ChatGPT with a broad prompt:

Prompt: I just got a Kindle, and I am curious if there are free books that I can use on Kindle, or are all books going to be purchases?

He received six suggestions, which included Libby, public domain sites, and Prime Reading on Amazon. Reading through them helped him narrow in on the options that felt most relevant and achievable. Reflecting on his approach, he explained:

“I'm starting wide with, like, this big umbrella idea. Using an AI model of some kind helps get me more specific, to then be like, what do I actually want? Or what am I actually thinking?”

This also allowed users to bypass a common frustration in traditional search: keyword foraging — the trial-and-error process of guessing which search terms yield useful results. By offloading that cognitive burden to AI, users could focus more on refining their goals, rather than reverse-engineering the right query.

AI Handles Multiple Constraints Better

Many of the information-seeking tasks conducted by the participants involved constraints — such as a budget, timeline, or location. These constraints are often difficult to include in traditional search queries, especially when several need to be considered simultaneously. One participant planned a golfing-themed bachelor trip for a group of four friends. He had multiple requirements:

• A 3-4 night trip with 3-4 rounds of golf

• Multiple golf courses in the area

• Budget under $1,000 per person

• Preferably close to his home state

Rather than beginning with a search engine, he opened ChatGPT. He began with a broad prompt.

Prompt: Best destinations for four-person golf trips under $1,000

He then refined his query, asking ChatGPT to exclude destinations east of the Mississippi.

“Whenever I have multiple constraints (...) ChatGPT is usually my go-to because ChatGPT seems to be able to handle three or four constraints better than Google can.”

(Although Google now has AI mode, this feature was relatively new in our study and underutilized due to its low discoverability.)

AI Saves Interaction Cost

Several participants mentioned that using AI saved them clicks that they would have had to spend visiting multiple websites to acquire all that information, and thus shortcut the task of information foraging.

“You get so much more information (...) I definitely am not getting that on Google without having to do multiple clicks. And I mean, I guess that's the value of ChatGPT or Gemini or Grok or any of those things (...) it just saves the user clicks.”

GenAI chatbots aggregate a lot of information and present only what’s relevant to the user’s query, saving users the interaction cost and cognitive load involved in doing the same work by themselves.

“I do prefer (...) an AI model answering this type of question… so much more research would have to be done if all I’m doing is clicking through these [Google search results] and none of these are actually giving me the type of specific response I would get in an AI.”

AI was especially helpful when scouring product reviews. Multiple participants asked for summaries of reviews in their information-seeking process. For example, one participant, who wanted to find out what people were saying about a particular car model she was considering buying, didn’t want to get caught up reading many individual reviews, which sometimes got too technical.

“Sometimes, it's just too much information (…) some people go in [to] so much deep details (…) I'm just like, ‘get to the point, is it worth keeping or not?’ So, I would probably [lean] (…) more towards the AI tool for [that].”

Instead of reading many reviews on Reddit or other sites, she preferred having Gemini go through all the reviews and give her an understanding of how people find the car. Another participant mentioned that this was why he uses Rufus on Amazon.

“I do feel like [Rufus] helps me aggregate information and not have to read through every single review of a product.”

The ability of AI to summarize many reviews and product information makes it a useful companion. One participant likened AI to a salesperson, but without the selling pressure.

“It was almost like talking to a knowledgeable salesperson that isn't trying to direct the conversation, that's letting me kind of direct the conversation and really dig in and explore what I want to learn about.”

AI Reduces Working-Memory Load

However, users frequently compare options across different websites or sources. To do so, traditionally, they would either keep all the candidate choices in their working memory or use some form of external memory, such as page parking or notes.

AI provides a convenient solution. We observed participants frequently using AI to consolidate information and make comparisons easier.

Information Aggregation Without AI

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