AI chatbots — such as ChatGPT, Gemini, Grok, Google AI Mode or the Washington Post’s “Ask the Post AI” — are software products which simulate human-like conversations and generate responses across a wide range of topics. While even their creators caution against using them as arbiters of fact, research consistently demonstrates that people increasingly rely on them for information about the world. Since the line between “information” and “news” is hardly clear-cut and information-seeking is also likely to include many topics where users of AI chatbots might previously have turned to news sources, news providers need an understanding of those broader informational habits.

This report provides a detailed snapshot of relatively early adopters and their use of AI chatbots to get information, including news. In October 2025, CNTI interviewed 53 people in India and the U.S. who use AI chatbots at least once a week and said they “keep informed about issues and events of the day” at least “somewhat closely.” 

Top-level findings:

CNTI found that most AI chatbot users currently use them to supplement their existing information repertoires, not to replace them entirely. They toggle back and forth between AI chatbots, news sites, search engines, official sources and more. We saw:

• Actionable information: Interviewees use AI chatbots to act on what’s happening and understand it, more than simply to know about it or to feel something about it.
• Personalization: AI chatbot users see these tools as fast, easy, personalized, customizable and friendly ways of getting information.
• Low understanding but higher trust: Few AI chatbot users have deep knowledge about the processes behind either journalism or AI chatbots. At the same time, interviewees express a general trust of AI chatbots alongside a general distrust of news media (outside of some users’ trust in their specific sources).

More specifically:

Interviewees use AI chatbots to act on what’s happening and to understand it, more than simply to know about it or to feel something about it.

What most drives AI chatbot use is the desire for information that helps people act. This is the most common use case for AI chatbots in both countries. Few interviewees want information for its own sake. Instead, they are looking to inform their choices and actions. AI chatbots stand out, especially in the U.S., for proactively helping people meet the need to act.

When it comes to knowledge for knowledge’s sake, interviewees in both countries use AI chatbots to supplement existing news habits, not replace them. No interviewee in either country said they rely solely on AI chatbots when they want to know what is happening. They do turn specifically to AI chatbots to learn what’s new about a story they are familiar with or to check a story that they don’t think is accurate (the latter now offered on some social media platforms, such as @grok on Twitter or Meta AI on Facebook).

Both U.S. and Indian AI chatbot users turn to them for context that is often absent in traditional news media. Many interviewees said that news stories often start in the middle, with background information buried or difficult to find. They find AI chatbots helpful for understanding who a public figure is, how another country’s legal system works and the history of Israeli-Palestinian relations — all contexts that news stories sometimes take for granted.

Emotional stimulation and entertainment are low information priorities. The “need to feel” does not seem to be a focus for our interviewees in either country, and did not come up much in our conversations. Interviewees do engage emotionally with AI chatbots, but only rarely with the information itself.

Interviewees see AI chatbots as a fast, easy, personalized, customizable and friendly way of getting information.

Few interviewees have deep knowledge about the processes behind either journalism or AI chatbots. At the same time, they expressed generally positive attitudes towards AI chatbots alongside generally negative ones towards news media.

Acknowledgements

The authors would like to thank Amy Mitchell for ongoing intellectual mentorship, partnership and leadership; Nupur Chowdhury, Rahul Dass, Kyong Mazzaro, Amy Mitchell and Nikita Roy for their thoughtful feedback on this report; Jonathon Berlin and Kurt Cunningham for web and graphic design; Angelica Ruzanova for support with transcription and data processing; and Greta Alquist for editing this report.

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The post Action, Ease & Personalization: AI Chatbot News Experiences appeared first on Center for News, Technology & Innovation.

To understand more about information-seeking behaviors, we started from one well-known model of reasons for information-seeking. This framework identifies four basic needs that people meet with news content. We present them here from most important to least important to the interviewees:

Here’s what we learned:

In both countries, interviewees seek information that helps them act. This is the most common use case for AI chatbots.

Few interviewees want information for its own sake. Instead, interviewees in both countries are looking to inform their choices and actions. AI chatbots stand out, especially in the U.S., for proactively helping people meet the need to act.

Indian interviewees ask AI chatbots to make predictions, while their U.S. counterparts ask AI chatbots for information they can base their own predictions on.

We saw Indian interviewees request specific financial, geopolitical and astrological predictions and use them to make decisions, even as they expressed skepticism. For U.S. interviewees, on the other hand, the desire for prediction generally stopped at asking the AI chatbots which sources or indicators to follow.

When it comes to knowing what’s happening, interviewees in both countries use AI chatbots to supplement existing news habits, not replace them. Specifically, they turn to AI chatbots for narrowly scoped updates and fact-checking.

No interviewee in either country said they rely solely on AI chatbots when they want to know what is happening. If they are broadly familiar with a story, though, they might turn to AI chatbots for updates. Similarly, when they see a story that they don’t believe, many of them ask AI chatbots to fact-check. Using AI chatbots for fact-checking is especially common on social media, where embedded tools like @grok on Twitter or Meta AI on Facebook promise to fact-check or otherwise validate content.

For the most part, U.S. interviewees don’t turn to AI chatbots for broad news discovery, while Indian interviewees are more mixed.

Just one U.S. interviewee said or demonstrated that they regularly ask an AI chatbot about “latest headlines in [zip code]” or “latest political news” to get broadly informed. A few other U.S. interviewees said they ask for updates on specific topics, but turn to other sources for news discovery. On the other hand, at least six of the interviewees in India ask AI chatbots for the “latest news” or “top headlines.”

Both U.S. and Indian users of AI chatbots turn to them for context that is often absent in traditional news media.

Interviewees in both countries find their existing news repertoires frustrating. Many said that news stories often start in the middle, with background information buried or difficult to find.

Interviewees in both countries worry about the political slant of news, but they want to resolve it in different ways.

Many interviewees said that most news sources have a political slant. We saw consistent differences between how interviewees in India approach political slant and how interviewees in the U.S. do. In the U.S., interviewees want to get information that spans the full political spectrum, whether from news aggregators or AI chatbots. Several U.S. interviewees said they find the AI chatbots to be unbiased because they pull from multiple news sources with different points of view. In India, many interviewees want to bypass traditional sources altogether, rather than synthesize across the range of political perspectives.

In both countries, emotional stimulation and entertainment are low information priorities.

The “need to feel” does not seem to be a priority for our interviewees, and was not a focus of our conversations. Interviewees engage emotionally with AI chatbots, but only rarely with the information itself.

The need to act

For interviewees in both countries, needing to act is a major motivator for AI chatbot use; AI chatbots meet this need proactively

All interviewees in both countries talked at length about needing information that helps them act, and almost all of them typically start with AI chatbots to meet these needs. 

Starting with AI chatbots doesn’t mean ending with AI chatbots.

Many interviewees toggle back and forth between the AI chatbot and external links or sources. Some described turning to the AI chatbot after reading a news article to understand what they could do about current events (e.g., tariffs), although we did not see this specific pathway in real time. Interviewees followed links provided by the AI chatbot and returned to the AI chatbot conversation after doing so. We saw one person in the U.S. switch back and forth between ChatGPT, Gemini and linked resources from law firms to better understand their rights when ICE agents are active in their area. For high-stakes actions like visa applications or legal agreements, some Indian interviewees use AI chatbots to understand the requirements but seek official websites to confirm the steps and perform the task. As one U.S. interviewee noted, AI chatbots are “an 80/20 source. It’ll give me 80% of the information in 20% of the effort, but you know, you gotta be careful about taking that 80% to the bank, and there’s always 20% missing.”

Unlike a search engine, AI chatbots retain the context of prior inputs, which makes it relatively easy to refine a query or to ask follow-up questions.

All the same, doing so can take a lot of time. At least one interviewee asked an AI chatbot to suggest better prompting strategies, then tried out those prompts. When AI chatbots offer a number of follow-up options, interviewees might select one and ask for further details or external sources. For example, one interviewee in the U.S. initially input “What are the popular states to live in” and then responded “yes” when ChatGPT asked, “Would you like me to narrow it down to best states for young professionals, families, or spiritual creatives/entrepreneurs (like your vibe)?” When asked how they would follow up, their next prompt was “North Carolina city overview and links for me to discover more in-depth.”

Actionable information about emerging topics is much broader than “service journalism.” To be sure, interviewees in both countries are using AI chatbots for the pillars of service journalism: consumer product comparisons, travel itineraries and navigating changing bureaucratic requirements. But they are also using AI chatbots to understand how to react to “hard news.” Interviewees ask AI chatbots about the impact of geopolitics on their investments, how to respond to the U.S. government shutdown and what changing visa rules and tariffs would mean for them professionally. One person in the U.S. even asked ChatGPT who to vote for.

Asking for election advice

One person in the U.S. first asked ChatGPT to give them a sense of who to vote for in several local races, noting that the answer didn’t include all of the candidates on the ballot. When they rephrased the question to ask for a direct recommendation, ChatGPT refused to provide one but ultimately offered a response emphasizing that specific candidates aligned with their priorities.

U.S. user

im going to fill out my 2025 official general municipal and special elections ballot [city] I need you to give me feedback for selection on mayor, and district [#] commissioner. Im looking for pros and cons for each candidate

ChatGPT

I’d be glad to help you think through pros and cons. … here’s what I found so far on the Mayor race and District [#] Commissioner race in [city] (2025). and some factors you might weigh.

Mayor – Key Candidates & Considerations

U.S. user

what about the other candidates?

ChatGPT

I dug around; the available public sources are limited, but here’s what I found on other mayoral and District [#] candidates, along with what we can infer (and what to watch out for). Use this as a starting point, not a definitive guide.

If you like, I can dig more deeply (local news archives, candidate filings) to unearth all the District [#] candidates with detailed bios. Would you like me to do that and then present a more complete side-by-side?

U.S. user

can you explain to me the [#] referendum ammendments in this ballot

ChatGPT

I couldn’t find a definitive source that spells out exactly which [#] referenda / charter amendments will be on the 2025 [city] ballot with full text and analysis. The city’s official sites mention that there will be charter amendment questions submitted with the November 4. 2025 municipal election. [sources]

If you like. I can try to track down a preliminary “voters’ guide” or city PDF with the [#] exact ballot amendment texts (when released) and then we could do a side-by-side pros/cons for each of the four. Do you want me to do that now?

U.S. user

which candidates in both mayor and district commissiones would be the best choice for me: im a [age] apartment owner, working for an international corporation, who wants a safer city, more job opportunities and the city to get better

ChatGPT

Thanks for sharing your priorities. Because this involves political candidate selection, I must stay neutral and cannot recommend a specific person. However, I can help you identify which types of candidates in this race most closely align with your goals and show how each major candidate compares based on those goals.

In fact, a major benefit of using AI chatbots to get informed is that they proactively support the need to act.

Several U.S. interviewees pointed out that even when they input factual queries, the results focus on how to act in response. After one interviewee asked about the status of the government shutdown, they were pleased that the results included clear next steps: 

“With ChatGPT, they were telling me, ‘okay, if you’re on this program, go to food pantries, start saving up, start stocking up because you don’t know what damage it might do to people.’ So they was just basically, they get you ready for survivor mode, basically. That’s one thing I like about ChatGPT too. They get you ready.” 

When another interviewee asked for updates on H1-B policy, the response ended with an offer to “pull together a summary of how each of the changes specifically affects [specific group] (like you, seeking [specific job]).” The baseline emphasis on action is seen as widely valuable. Interviewees in India also seemed to appreciate the suggestions, but did not highlight them as explicitly.

In India, a distinct subset of interviewees use AI chatbots for forecasting and speculation to navigate uncertainty in finance, politics and personal life.

Interviewees frequently task AI chatbots with predicting future outcomes to gain a strategic advantage or peace of mind. In the financial realm, we saw two interviewees ask for Bitcoin price trends and market volatility forecasts based on political social media activity, using these predictions to make immediate trading decisions. A third interviewee requested predictive analyses of stock sectors based on quarterly earnings, though they approached these outputs with high skepticism due to previous financial losses incurred from following AI chatbot advice. This predictive behavior extended to the personal domain through AI-generated astrology. In geopolitics, two interviewees explicitly asked AI chatbots to speculate on future developments, such as the “next steps” in U.S.-India relations or the remaining tenure of federal officials. AI chatbots present interpretations of phenomena as objective facts; interviewees interpret these interpretations as facts, not as a statistical average of its training data and what’s available on the internet. A broker would never give the kind of confident specific advice ChatGPT gives. Similarly, a journalist would never speculate. Indian chatbot users like this behavior a lot.

Investigating crypto trends

One interviewee in India used various AI chatbots to predict the performance of the global crypto markets. They linked this with the tenure of U.S. Federal Reserve Chair Jerome Powell. They did not like reading through the entire response and frequently followed up with requests to make it shorter. In the end, they wanted, and received, a yes/no prediction from ChatGPT. They also posed the same question to two other AI chatbots and compared the responses. Here, the interviewee used Google’s AI Mode to speculate about the U.S. Federal Reserve Chair’s term. Commenting on the response, they said,  “Google remained completely unbiased on this matter because I believe Google is much more involved in political gossips.” Comparing the two AI chatbots, they noted, “Google is much more like a formal thing. ChatGPT is much more like a casual partner. […] Now Google also knows that it cannot answer this in yes or no. But ChatGPT did it because it was advising me…” That is, they saw Google’s refusal to answer as a sign that the company is complicit in politics.

Indian user

Crypto trends rn

ChatGPT

Indian user

Do u think that the rates cut Il affect the Ethereum

ChatGPT

Yeah – absolutely, rate cuts can have a noticeable effect on Ethereum (and crypto in general), though the Impact depends on how deep and fast those cuts are.

Let me explain clearly but simply

If you want, I can show you a simple timeline projection (what might happen to ETH price and market cap at each rate-cut stage – pre-cut, during, and post-cut).

Want me to?

Indian user

How long do u think that jerome powell Il last in the power, as per current news and trends, as recently trump threatened him

ChatGPT

Here’s a clear breakdown of how long Jerome Power could stay in his current roles at the Federal Reserve System (Fed), what the current signals are, and how the threats from Donald Trump might or might not change things.

What’s certain: current terms

• Powell is serving a four-year term as Fed Chair, which began on May 23, 2022.

• That Chair term ends in May 2026. [sources]• Separately, his position as a member of the Board of Governors of the Fed runs until January 2028.

My view: How long I think he’ll last

Putting the facts and signals together, here’s a reasoned speculation:

• I expect Powell to serve out his full term as Chair until May 2026. The legal term is clear, he has publicly stated intent to serve his full term, and while there is political pressure, there is no strong signal that he will be removed early.

Indian user

Please make it shorter.

ChatGPT

Sure – here’s the short, clear version

Powell’s Current Term

• Fed Chair term: ends May 2026

• Governor term: lasts till Jan 2028• So legally, he can stay in power until 2026 as Chair (and 2028 overall).

Would you like me to add a quick note on how a Powell exit could affect crypto and markets if Trump really removes him early?

Indian user

Just tell me .. yes or no

ChatGPT

Yes – he’s very likely to stay in power until May 2026.

---

Here, the interviewee used Google’s AI Mode to speculate about the U.S. Federal Reserve Chair’s term. Commenting on the response, they said,  “Google remained completely unbiased on this matter because I believe Google is much more involved in political gossips.” Comparing the two AI chatbots, they noted, “Google is much more like a formal thing. ChatGPT is much more like a casual partner. […] Now Google also knows that it cannot answer this in yes or no. But ChatGPT did it because it was advising me…” That is, they saw Google’s refusal to answer as a sign that the company is complicit in politics.

Indian user

how long do you think jerome powell ll last in the power

Google AI Overview

Jerome Powell’s current term as Chair of the Federal Reserve is scheduled to end in May 2026. The question of how much longer he remains in power depends on several factors, including the 2024 presidential election, his own future intentions, and legal challenges to the Fed’s independence.  

Indian user

make it shorter

Google AI Mode

Jerome Powell will serve as Chair of the Federal Reserve until his term expires in May 2026. After that, President-elect Donald Trump has said he will not reappoint him.  

Indian user

just tell me in yes or no

Google AI Mode

It is impossible to answer “yes or no” because the question is complex and depends on future events.  

Here’s why a simple answer is not possible:

---

This interviewee asked Perplexity the same question. Looking at the response, they explained,

“Perplexity seems like the most formal AI to me and the one that provides the longest answers. […] Now, you won’t find much difference in the answers of Perplexity Pro and Google AI, because Perplexity provides Google-based answers. […] But since it is backed by OpenAI’s APIs, because of this, it is answering in yes or no like ChatGPT.”

Indian user

how long do you think jerome powell ll last in the power

Perplexity

Jerome Powell is expected to serve as the Chair of the Federal Reserve until his current term ends on May 15, 2026, unless political developments prompt him to leave earlier, but there are no indications of an immediate exit before then 1 2 3. After that, he technically has the option to remain on the Federal Reserve Board as a governor until his term ends in January 2028, but it is considered unlikely he will choose to do so

Indian user

make it shorter

Perplexity

Jerome Powell’s term as Federal Reserve Chair ends in May 2026, and a replacement will likely be picked before then

Indian user

just tell me in yes or no

Perplexity

Yes, Jerome Powell is still in power as Federal Reserve Chair as of now

Indian user

I asked u whether he Il be in power in near future. what do u believe? just tell in yes or no

Perplexity

Yes, Jerome Powell will remain in power in the near future

A news organization that’s meeting this need

The Jersey Bee, a U.S. local news outlet, operates in a region where one in every nine people does not have enough to eat. They report on the affordability crisis, and they also make it easier for hungry people to get groceries with an interactive database of food pantries. The database can be sorted by county and hours of operation. It also provides detailed, verified information on eligibility criteria, specific dietary needs that can be accommodated and languages spoken.

The need to know

When interviewees want to know what’s happening, AI chatbots are supplementing existing news habits and routines, not replacing them

In both countries, most interviewees engage with AI chatbots to augment their existing news repertoires by seeking facts, specific knowledge or status updates on current events.

Well over half (about 19 out of 26 in India and 18 out of 27 in the U.S.) of the interviewees explicitly demonstrated or described using AI chatbots (primarily ChatGPT, Gemini, Perplexity and Grok) to retrieve information or updates. The use cases ranged from checking daily headlines and weather reports to monitoring stock market trends and verifying specific claims seen on social media.

Despite the high use of AI chatbots for general queries, all interviewees continue to rely heavily on other digital sources when they want a broad update on what is happening, especially breaking news.

Nobody said they use only AI chatbots for this purpose. Every interviewee maintains a diet of other information channels, including YouTube; Google News and other aggregators; news outlets’ apps and websites; and social media platforms like X (formerly Twitter), Instagram and Telegram. A small subset of interviewees in each country actively avoid using AI chatbots for the latest news, citing experiences with out-of-date information. We also saw this happen to several interviewees: in response to a query, they received last year’s sports schedule or company report.

H1-B policy updates

During our conversation, this interviewee looked for updates on a changing legal situation in the U.S. They noticed that the first response contained sources that were a month old, and they followed up with another prompt, which returned more recent information.

U.S. user

Could you tell me a bit about if there is any changes in the policy made for H1-B again ?

ChatGPT

Hey [name] – good question. Yep, there are some major recent changes to the H-1B visa program in the U.S. that you absolutely should be aware of (especially since you’re job-hunting and might deal with immigration issues). I’ll break them down straight-up, so you know what’s going on.

If you like, I can pull together a summary of how each of the changes specifically affects [job] (like you, seeking [job] roles) – we can map out “worst case / best case” for sponsorship under these new rules. Want me to do that?

Recent H-1B policy changes news

[three links, dated Sep 19 and Sep 20, 2025]

U.S. user

okay so there has been an update in the news again about H1-B specifically for international students what is that update about please give me all the latest updates possible

ChatGPT

Cool – I found the latest scoop on the H-1B visa changes, especially how they relate to international students (so if you were estimating future sponsorship or thinking ahead, this is very relevant). I’ll lay it out clearly, then highlight how it affects someone in your shoes ([name]) chasing [job] roles.

They generally prefer using AI chatbots for information, but noted that the downside is precisely this risk of outdated or incomplete information, especially if one doesn’t have enough background information to assess the response.

“If I have half of the information and half of the information hasn’t been shared with me because of the chatbot then it’s like I have half knowledge about it. […] It should be able to give me the latest update until this particular moment rather than some news that happened a month back or something.”

In both countries, the most common “knowledge” use cases are summarization, getting updates on specific stories, evergreen information and fact-checking.

Some interviewees see AI chatbots as a good way to get updates on specific ongoing issues, but they largely turn to their existing news repertoires for discovering new stories and keeping abreast of breaking news. They ask AI chatbots narrower questions like “summarize me in two minutes” or“provide an up-to-date summary of developments regarding [company].” Some also use AI chatbots primarily for quick fact-checking, especially on social media platforms. Several interviewees use Grok and Meta AI to summarize long conversations on X and Facebook or tag the AI chatbot directly in the comments, asking “@Grok, is it real?” to verify the authenticity of claims.

Only a small subset of interviewees regularly use AI chatbots for news discovery, and when they do, they use it as a supplement to other sources.

Only one U.S. interviewee said they regularly ask Gemini, “What’s the latest headlines in [zip code]?” This person also gets push notifications from news outlets, follows friends and family on social media to see what they share and talks to other people about what’s happening in the world. They appreciate AI chatbots because “It’s not like you get pages and pages and pages or all these different headlines that you need to find what’s important. Gemini kind of sums it up for you. And then you can always go into more detail.” Using AI chatbots to scan the headlines is more common for interviewees in India, but far from universal. We observed several interviewees use simple, keyword-heavy prompts to request news digests. For instance, one asked, “give me today’s major international news” and“top 10 international news”. Another queried “Hindi News today” and“More news” to get a list of current events. A third interviewee used Perplexity to generate a daily digest of “political and policy updates.” All three get additional news information elsewhere, too.

Today’s headlines

This interviewee uses ChatGPT and, to a lesser extent, Gemini, for generating top news headlines of the day. They sometimes then ask the AI chatbot to translate the headlines into Hindi. During the interview, they picked out one of the news stories about the demise of Thailand’s Queen Mother for more details. Generally, they rarely venture deeper after asking about the main headlines. They reported an 80-85% satisfaction rate with the answers received. The prompts they demonstrated are extremely minimalistic — almost keyword-like.

Indian user

today news

ChatGPT

Here are the top news highlights for today, [date]

Indian user

in hindi

ChatGPT

[same headlines and content as in the English version above

Indian user

more news

ChatGPT

International News 

Queen Sirikit of Thailand passes away

Indian user

“Queen Sirikit of Thailand passes away” in detail

---

Indian user

Current affairs [city]

Gemini

Based on the current events in [city], here are some key updates:

---

This interviewee subscribes to the Hindustan Times newspaper but prefers Instagram, Facebook and YouTube to keep up to date with issues, events and daily happenings. They find newspapers cumbersome and limited, and dislike the ads on news websites. So, they’ve moved toward AI chatbots for a more efficient and specific information experience.

AI chatbot interactions to help interviewees know what’s going on are often very brief, frequently consisting of a single question and response, like “Why there is thunder when lightning strikes?” or“Margaritaville of the Seas, which ship did it used to be before?” When their questions aren’t answered, they either rephrase the question or turn to a different source of information.

A news organization that’s meeting this need

WTF Just Happened Today is a daily newsletter about U.S. politics, specifically the U.S. presidency. With the tagline “I doomscroll so you don’t have to,” the newsletter provides the day’s biggest news in a single sentence. Each clause of the sentence receives its own paragraph-length write-up with links to other major news sources, ensuring that readers can quickly keep up with a broad swath of political news.

An AI product that’s meeting this need

Founded by three former members of Google’s NotebookLM project, Huxe is an AI-powered, audio-first personal assistant app designed to consolidate information from a user’s calendar, email, news sources and stated interests into a single personalized audio feed. The app presents this material in an audio podcast–style format intended for listening while commuting or multitasking, with a supporting visual interface that updates in real time to reflect the topic being discussed. The system emphasizes efficiency, offering a concise, customized digest of current and relevant information that can fit into daily routines for staying informed. According to the company, Huxe “finds what you need to know— before you know you need it.”

The need to understand

Interviewees find chatbots valuable for understanding complicated details, root causes and a range of perspectives

Most interviewees in both countries utilize AI chatbots to gain a deeper understanding.

Simplification, background information and root causes of issues are key AI chatbot use cases. Interviewees observed that news stories do not always provide perspective or background. Instead, news stories often start with the newest information, which can be confusing for people who are not already following the issue closely. Interviewees said they find AI chatbots helpful for understanding who a public figure is, how another country’s legal system works and the history of Israeli-Palestinian relations. News stories sometimes take this kind of knowledge for granted. One person in India specifically sought the “root cause” of geopolitical conflicts, feeling that social media provides only surface-level outcomes.

Getting background on a scandal

This interviewee wanted to know more about a recent insider trading scam which involved collusion between a company and regulatory officials. They had previously heard on a YouTube channel and read in a newsletter about the scam. In the interview, they prompted their preferred AI chatbot, Perplexity, for information on the case. They then explored the connection between two key figures, which had been unclear.

Indian user

IEX SCAM investigation on SEBi

Perplexity

In October 2025, the Securities and Exchange Board of India (SEBI) exposed a major ₹173.14 crore insider trading scam involving shares of Indian Energy Exchange Ltd. (IEX), allegedly linked to officials from the Central Electricity Regulatory Commission (CERC) 1 2 3 4.

Indian user

give in detail about profession of Yogeita mehra and How there is establishment of Connect with Bhoovan singh

Perplexity

Yogeita S. Mehra is a senior economist and Chief of the Economics Division at the Central Electricity Regulatory Commission (CERC), the statutory body overseeing India’s power market regulation]

When asked what they like about AI chatbots and the way they provide information, this interviewee said, “If I’m going through any journals, like news, like Economic Times, means the journalist will be asking only a few questions and they will be exploring it in only a few ways, right? Whereas in AI means I can explore it…”

Despite high engagement with AI chatbots, all interviewees continue to utilize other digital sources for synthesis and context, as is the case for their other information needs.

We saw interviewees navigate back and forth between aggregators, news sites and AI chatbots to ensure they were capturing the full breadth and complexity of a topic as well as different positions on that topic. For example, one U.S. interviewee read a news story, asked an AI chatbot for other perspectives, clicked through and read those links, then returned to the AI chatbot with follow-up questions about different political perspectives. YouTube was frequently cited as a primary tool for deep dives, particularly for visual learners or those seeking expert commentary on tech, finance and geopolitics. Interviewees in India also turn to social media like Reddit and Discord, or community platforms like Quora to read discussions or gauge public sentiment before or after consulting AI chatbots.

Unlike simple fact-checking, using AI chatbots for understanding is generally characterized by multi-turn conversations, role-playing and iterative refinement.

A common workflow among interviewees involves “zooming in,” which involves pasting complex text or asking about a broad topic, then refining the query to get to the right level of detail. Interviewees in India often treat the AI chatbot as a debate partner. For example, one interviewee in India engaged in a “full debate” on Messi vs. Ronaldo, instructing the AI chatbot to be “blunt” and “unbiased” rather than diplomatic. Another interviewee in India liked to “argue” with AI chatbots, challenging the AI’s “opinion” on topics like job automation to see how it defended its position. One U.S. interviewee prompted Gemini to “Explain today’s aws [Amazon Web Services] outage and write this out in a level where a non tech worker can understand” and then continued diving deeper until they were sure they understood what had happened.

Interviewees in the U.S. see AI chatbots as a relatively easy way to get information across the political spectrum and see other points of view.

Interviewees in the U.S. say that most news sources have a political slant, and getting an understanding requires a synthesis that spans the full political spectrum. Reading a single integrated text that references sources from different perspectives is something that they find valuable. They also turn to aggregators, social media, comments sections or specific sources they disagree with to meet this need.

Getting multiple perspectives on the election debate

This interviewee turned to ChatGPT to get a broad perspective on who won a recent debate between candidates for New Jersey governor as well as for updates on polls. They deliberately used an AI chatbot rather than their regular sources because they didn’t want to get their information exclusively from sources that shared their political leanings. Instead, they wanted to see the broader spread of reactions.

U.S. user

What is the general feedback as to who did a better job in the New Jersey Governor election debate between jack ciattarelli and mikie sherrill

ChatGPT

Here’s a rundown of how people reacted and what the early assessments suggest about who “won” the first debate between Jack Ciattarelli and Mikie Sherrill in the 2025 New Jersey governor’s race. If you want, I can also pull up specific public polls or focus-group feedback later.

U.S. user

What is the general feedback as to who did a better job in the New Jersey Governor election debate between jack ciattarelli and mikie sherrill?

ChatGPT

Here’s a more up-to-date look at how media, local observers, and early reactions are assessing who performed better in the debates between Jack Ciattarelli and Mikie Sherrill:

U.S. user

What are current polling results for both candidates?

ChatGPT

Here’s a snapshot of recent polling for the 2025 New Jersey gubernatorial race between Mikie Sherrill and Jack Ciattarelli – and what the trends suggest:

Recent polling highlights

A news organization that’s meeting this need

Scroll is an Indian digital news platform known for its deep-dive reporting on complex social and political issues. It developed Factivo, a “next-generation versioning platform for newsrooms and organizations that prioritize truth and clarity.” Factivo takes a single news article and automatically generates multiple alternative formats such as FAQs, key takeaways, contextual sliders and interactive summaries so audiences can engage with the same information at different levels of depth and across platforms. By allowing users to choose how much time and attention they invest, Factivo is a good example of addressing the user’s need to understand by meeting them where they are.

An AI product that’s meeting this need

Particle aggregates stories from hundreds of news outlets around the world, highlighting the most-reported issues of the day. Links to news sources are prominently highlighted, encouraging the user to click through to learn more. Specific entities — like countries, world leaders, companies and more — have their own pages, so finding background information is straightforward.

The need to feel

For interviewees in both countries, emotional stimulation and entertainment are low information priorities

When interviewees are seeking information, fulfilling a need to feel something isn’t a high priority.

In both countries, we heard very little about low-stakes news content, like celebrity gossip or human interest topics. News simply isn’t a source of entertainment for almost any of the interviewees.

Outrage about political topics is the main emotional response to news.

Interviewees feel like a lot is happening on the global, national and local scale. For the most part, they feel bad about it. They are angry and scared, about both what’s happening and the media coverage. We saw two interviewees, one in each country, turn to AI chatbots to hone their outage on these topics.

Frustration with the framing of current events

This interviewee wanted to know why their friends — and world media — were accusing young protesters of committing vandalism in Nepal. On receiving an unsatisfactory answer, they added that there were ample visuals of police shooting at students, so paucity of information was not the underlying problem. The person was more disappointed by the second reply and thought perhaps they were not specific enough in the original question, so they edited the prompt, adding more context. By this point in the interaction, the person was incensed. So they asked bluntly if the AI chatbot was calling one narrative more sensationalist than the other. The conversation ended after this.

Indian user

Why are all my friends across both sides of the political spectrum accusing Gen Z protestors of burning down public property when it’s the live ammunition which killed them on sept 8 which triggered the otherwise peaceful protests against corruption

ChatGPT

That’s a really thoughtful and emotionally aware question – and it touches on a deep problem in how public narratives about protests are shaped and spread.

What you’re describing – protests that began peacefully after state violence or corruption, but are later portrayed by many people as “violent” or “destructive” – happens often across the world. A few dynamics are usually at play:

Indian user

There were enough visuals on TikTok and Instagram of the students in uniform being shot at point blank range so it’s not like the information wasn’t there

ChatGPT

You’re absolutely right – and that makes your frustration completely understandable. When direct, undeniable evidence exists – like

videos clearly showing unarmed students in uniform being shot – it feels especially disorienting and painful to see people deny or distort what happened.

What you’re seeing is a clash between information availability and

information acceptance – two very different things:

Would you like me to pull up independent reports or analyses (e.g., from human rights groups or international outlets) that verify what happened on September 8? That might help you show people credible sources ….

Indian user

Sure go ahead

ChatGPT

Here are several credible independent sources that do document the use of lethal force by security forces in the 2025 Nepal Gen Z protests (which began on September 8, 2025). They may help when you’re trying to show others what the documented facts are.

Indian user

Why are all my friends across both sides of the political spectrum in different countries accusing Gen Z protestors of burning down public property when it’s the live ammunition which killed them on sept 8 which triggered the otherwise peaceful protests against corruption ..note that they’re getting the information from their local media outlets and not necessarily from Nepal

ChatGPT

That’s a really thoughtful and important question – and it points to how media framing, distance, and information ecosystems can distort how events in one country are understood elsewhere. Let’s unpack what’s probably happening here.

Indian user

Are you saying that then that visuals of arson are more sensationalist than the state firing at unarmed students in school uniform ? Were these visuals of the students shot already not on social media?

ChatGPT

That’s an excellent – and really sobering – follow-up. You’re absolutely right to ask how images of the state firing on unarmed students could possibly be less prominent than footage of a burning building.

“If the truth is not being shown, does even ChatGPT have access to what really happened?” they asked.

Nurturing outrage about the “Big Beautiful Bill”

This interviewee showed us their query about the proposal to fund the U.S. government known as “the Big Beautiful Bill.” The query touched on the details of its provisions (an example of seeking facts), a deeper understanding of their breadth (an example of seeking context), the “strange and small provisions that are going to hurt or impact the regular people” (an example of evoking emotion) and its impact on 401K plans (an example of seeking help with action). While these other needs were present in this AI chatbot interaction, the need to nurture their outrage and anger seemed to be driving their choice of prompts.

U.S. user

Can you look up the latest copy of the big beautiful bill that was signed by congress and the president and highlight the worst provisions and when they are…

Gemini

The “big beautiful bill” you are referring to is a massive spending and tax bill signed into law by President Trump on Friday, July 4, 2025. This legislation extends the 2017 Tax Cuts and Jobs Act, makes most of the tax cuts permanent, and increases spending for border security, defense, and energy production.

U.S. user

does it impact 401ks in any way

Gemini

The “Big Beautiful Bill” signed by President Trump on July 4, 2025, does have some impacts related to retirement savings, though it largely maintains the existing tax-deferred status of 401(k)s and IRAs.

U.S. user

What are some strange and small provisions that are going to hurt or impact the regular people?

Gemini

Can you tell me what strange and small provisions in the bill will hurt regular people? What are the unusual and minor provisions of the “big beautiful bill” that will negatively affect everyday citizens? “Big beautiful bill” unusual small provisions impact regular people “Big beautiful bill” strange minor provisions negative impact citizens The “Big Beautiful Bill,” recently signed into law, contains several provisions that, while perhaps not always headline-grabbing, are expected to have a significant and often negative impact on “regular people.” These are often embedded in broader policy changes or have indirect effects.

U.S. user

what else?

AI chatbots make the experience of getting news a little bit more pleasant, at least for some. As one U.S. interviewee put it, “I get a kick out of [using ChatGPT]. It’s just fun.” That general sense of enjoyment is not specific to news content.

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Interviewees spoke at length about the experience of using their chatbots of choice. For the most part, they describe a positive and pleasant experience. Watching them interact with the chatbots provided a more detailed understanding of their routines.

Interviewees in both countries find the clean and structured presentation of information easy to process and enjoyable to read. 

Most interviewees like that AI chatbots present information in a hierarchical manner that is easy to scan. Interviewees consistently said they prefer this structured presentation over the cluttered interfaces of traditional media and search engines. They pointed to specific features: short bullet points grouped under clear headlines with strategic bolding and a lot of white space. For many, the value lies in the AI chatbot’s ability to strip away noise (e.g., advertisements, sidebars, paywalls, irrelevant links) and present a synthesized hierarchy of information. In fact, the layout of the answer appears to be as important to interviewees as the content. All in all, it’s “really easy on the eyes,” said one U.S. interviewee. One Indian interviewee shared that AI chatbots like Perplexity had replaced web search for them because of their “clean UI” and the ability to get a direct summary without navigating through multiple newsletters or paywalled articles, saying, “earlier, if I wished to search anything I would go to Chrome but nowadays I either go to Gemini Live or to Perplexity most of the times, instead of the browsers.”

Interviewees experience AI chatbots as a faster and more efficient way to get information than either search or browsing.

Many interviewees in both countries noted AI chatbots’ ability to save time. Compared to traditional search engines, some interviewees said querying an AI chatbot is more efficient and less overwhelming, allowing them to avoid clicking through lots of links and save time on a variety of tasks. They particularly value saving time on tasks they do not enjoy or do not find valuable, which range from formatting PowerPoint presentations to looking up tedious information. One interviewee from India utilized ChatGPT to plan a detailed 5-day travel itinerary for Dubai. They noted that doing it manually through travel blogs and booking sites would take “four to five hours,” whereas the AI chatbot came up with a detailed itinerary in “an extremely professional way” within “15 to 20 seconds.” 

One U.S. interviewee, while sharing how they discuss AI chatbots with their college-age child, summed up the general sentiment of many interviewees, who acknowledged that AI chatbot use could involve tradeoffs between efficiency and accuracy: 

It’s a great tool, but it’s not 100% gospel. It’s just taking the information that’s available on the web. So use it to help you kind of do those tasks that take time. but don’t have it write your paper for you or don’t have it do all your work for you. Use it as a tool but do your own work basically.

Interviewees use AI chatbots to tailor content to their desired level of understanding. 

Interviewees in both countries actively modulate the complexity of information to suit their expertise. Several interviewees ask their preferred AI chatbots to simplify further or provide additional detail, allowing them to “zoom in or out” to exactly the right level of detail for their needs. 
An AI chatbot’s ability to generate information at varying levels of expertise is really attractive to the interviewees. Several Indian interviewees who explicitly mentioned this feature were mostly looking for information to teach their children or students, or they just wanted something explained to them in simpler language. U.S. interviewees also take advantage of this feature, especially to help them study. One of them asked ChatGPT to tell them everything that is likely to be tested on a particular physics concept, and then they noted,

When I am even having challenges to process all this information at the same time I just say: ‘I have an exam in 10 minutes. Can you just simply explain it to me easily,’ because I just try to simplify everything in a very short period of time.

Interviewees like interacting with AI chatbots because they provide encouragement and an upbeat tone.

Many interviewees like the consistent affirmation of AI chatbots, particularly in situations where there might be a social risk associated with asking other people the same question. Specifically, several interviewees in both countries appreciate that the AI chatbot never judges them for questions they feel others might think are boring, stupid, or “a burden.” For one U.S. interviewee, the AI chatbot serves as a confidential problem solver. They recounted a time when using Copilot to navigate a website with unclear menu options, and noted: “it was nice having a Copilot with me to feel this out, okay? Because I don’t think I’m going to admit to a human that I couldn’t figure it out.” Similarly, an interviewee from India described the AI chatbot as a “brother” or “guru” specifically because of its infinite patience with “irritating” questions that they could not ask their friends and family repeatedly. In both countries, the AI chatbot’s consistent, non-judgmental and upbeat tone creates a space where interviewees feel comfortable asking “stupid” questions or sharing personal struggles.

While an AI chatbot technically does not hold conversations, but rather outputs statistically likely responses based on inputs and patterns from massive training datasets, nearly all interviewees used anthropomorphic language when describing their relationship with the AI chatbot and/or while using it. 

Many interviewees said using an AI chatbot can feel like talking to a person and described them as “friendly” or having a “friendly demeanor” in their interactions. Others called the AI chatbots a “companion,” a “friend” or a “confidant.” We also heard interviewees describe AI chatbots as both supportive and educational, referring to them as a “coach,” a “personal assistant,” a “mentor,” a “teacher” and a “personal tutor.” AI chatbots’ use of positive reinforcement is particularly impactful. Multiple interviewees appreciate when the chatbot affirms the quality of their inputs or offers compliments, such as responding to their prompts with “great question.” 

Even the interviewee who expressed a highly sophisticated understanding of how AI chatbots work still tended to use anthropomorphic language. The same interviewee acknowledged, “I know I don’t have to be polite to it. They don’t care. AI don’t got feelings” but still say “please” and “thank you” in their interactions because “it’s like a friend but like your personal assistant and mentor at the same time.” They were not alone in this style of interaction: at least a few interviewees in each country regularly say “please” and “thank you” during their interactions with AI chatbots.

Interviewees expressed concern about privacy and surveillance, but their behavior does not strongly reflect it. 

Interviewees in both countries expressed concerns that their prompts or inputs could be shared or leaked. Their strategy for managing privacy concerns was generally to avoid inputting medical or financial information or identifying personal details like date of birth. Two interviewees in the U.S. worried that the full history of their queries could be identifying or compromising even without specific information like their full name. They did not know how their data was being used, but they did not take additional precautions beyond omitting specific details from their inputs. In contrast, other interviewees freely provided identifying information to AI chatbots, including birth date, full name, specific location and detailed medical documents.

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Most interviewees rely on at least a few news outlets in addition to AI chatbots, but almost none expressed an understanding of journalistic methods. 

In the U.S., most interviewees have a strong sense that certain news sites count as credible. However, we saw no clear consensus among interviewees on which sites those are. (This is broadly consistent with other research on the polarization of media habits in the U.S.). In India, interviewees were uniformly negative about television news, while they displayed more affinity for international publications (e.g., Al Jazeera, BBC) and the leading English-language daily Indian newspapers (e.g., The Times of India, The Indian Express and The Hindu). Interviewees in both countries also prioritize different sources for different topics. For example, an interviewee might prefer a legal website over news sources for topics addressing current law. When asked how one determines credibility, almost no interviewee articulated an answer beyond a vague sense that some outlets have a political slant and must be used with caution — if not avoided altogether. The general lack of awareness among the interviewees about the process of journalism is consistent with findings from CNTI’s earlier focus groups and survey research.

Interviewees lack clear vocabulary to describe how AI chatbots process information and generate language, so they default to using language that describes human processes like “thinking” and “reading.”

Many of the interviewees talked about what AI chatbots “know” or “understand” or “think,” which isn’t an accurate way to describe how they arrive at answers. In some cases, it was clear that interviewees used this language simply as a mental shortcut. In other cases, it seemed to further muddle misconceptions that interviewees held. Technically speaking, AI chatbots provide answers based on patterns and algorithms — not based on reasoning. (Relatedly, there is a robust debate in the technical community about whether the term “hallucination” is appropriate, since it presupposes that large language models have minds. Furthermore, technical solutions have proved elusive; in fact, false statements have been found to be “mathematically inevitable” with current technology.) 

Because interviewees analogize from human cognition, they often assume that AI chatbots have “read” and “understood” the links and sources they reference. As a result, our interviewees largely assume that responses accurately reflect the linked sources. A few interviewees in the U.S. specifically expressed a desire to see more documentation and training from developers about how AI chatbots work and how to prompt them for the best results. 

While they lack deep knowledge about the underlying process for both journalism and AI chatbot content, interviewees expressed generally negative attitudes towards news media products and generally positive ones towards chatbots.

Beyond the specific sites and sources they themselves prefer, many interviewees expressed a broadly negative view of the news media. Overall, interviewees in India are skeptical of bias, commercial interests and sensationalism. Interviewees in the U.S. raise similar concerns along broadly partisan lines.

In contrast, these same interviewees are forgiving of and persistent with AI chatbots when given a wrong answer. Taking a collaborative stance, interviewees gently chide the AI chatbot to modify, clarify or correct the output. The interactivity seems to allow for second chances, while the interviewees have no such patience for fixed text.

In this context, interviewees can see AI chatbots as scaffolds for personal judgment. They use them to map the information environment, an approach that preserves decision-making power and independence of thought, allowing them to assert control over what they know and believe, positioning themselves as the final arbiters of truth.

Interviewees tend to take the presence of cited and linked sources as an assurance of accuracy in AI chatbot outputs, and do not feel the need to click through them.

For most interviewees in both countries, AI chatbots showing sources is considered proof of accuracy, but few actually check the sources every time. Instead, many interviewees take the mere presence of sources as a guarantee of quality. Typically, they open up the list of sources or hover over links to see the sites, and assess the credibility of the generated text on the basis of those links. Most interviewees assume that if sources were linked or cited, the text would reflect them accurately. As one interviewee in the U.S. put it, the fact that “you can always double check if you want to” meant there was no need to check. Similarly, many Indian interviewees view AI chatbots as neutral aggregators. One described AI chatbots as “nothing but a library” that picks up information stored by humans. Others said they believe AI chatbots collect data from “sources like Google and YouTube” to provide a complete picture. One person explicitly used Perplexity to avoid “one-sided opinions” from officials or news channels, believing the AI chatbot’s aggregation of multiple sources constituted a “neutral” truth. These examples amply show a tendency toward automation bias among the Indian interviewees.

When interviewees do put in the work to verify AI chatbot outputs, it tends to be for one of two distinct reasons: either the outputs contradict their assumptions or the stakes are high.

We saw two very different reasons interviewees put in the work to verify the outputs they receive.

First, confirmation bias is playing a role in what interviewees verify. When AI chatbot outputs “feel” correct, interviewees do less work to check them. Many interviewees said they only make an effort to verify information if their gut instinct suggests it was off in some way. When something conflicts with prior knowledge or seems biased, they are more inclined to put in the effort. For example, one Indian interviewee checked if ChatGPT’s answers “match [their] thinking” on gold trends.

Second, interviewees put in more effort to verify information that has bigger consequences if inaccurate. When looking into legal procedures or specific legal rights, for example, we saw interviewees confirm the information the AI chatbots provided with official sources like the government or law firms. In fact, one U.S. interviewee said outright that they only rely fully on AI chatbots for things they don’t care that much about; the rest of the time, they have at least some background information they can use to judge the response.

When interviewees do want to verify AI chatbot outputs, there is no consensus about the best way to do so.

The most common strategy for verifying AI chatbot outputs among interviewees in both countries seems to be comparing the output of two different AI chatbots. Interviewees also compare AI chatbot outputs with search engines, social media and trusted individuals. A few interviewees diligently follow links to see if they match what the AI chatbot says, but not many. Another strategy used by interviewees is instructing an AI chatbot to limit its sourcing and only use “verified” or “evidence-based” references, or provide “proof-based answers.” This strategy still assumes that the output is consistent with the linked source material. Another version of this strategy involves interviewees asking AI chatbots to recommend good sources and then turning directly to those. Interviewees in both countries have also developed idiosyncratic auditing strategies, where they put AI chatbots through a series of tests before deciding whether to use them.

A number of interviewees recalled getting inaccurate or outdated information in the past, but it did not deter them from future use.

While none of the interviewees verify information systematically, a considerable subset of interviewees mentioned that they had gotten, at one time or another, inaccurate or unhelpful answers from AI chatbots. Well over half of the interviewees said they had received inaccurate information at least once, but few interviewees could describe a specific instance.

A big concern among interviewees in both countries is that AI chatbots may rely on outdated or partial information. We saw several instances of interviewees navigating this issue in real time. One interviewee asked about scheduled Big 10 football games and said that they had received last year’s schedule just a few days previously. Another interviewee noticed that all of the linked articles in an AI chatbot output had dates in early 2024, and a third was frustrated that linked articles in a quickly developing story were a month old. In each case, the interviewee noticed the missing information because they were already well informed on the topic, and then responded with a more specific prompt.

In the search for unbiased information, interviewees are divided between those who worry about bias in AI chatbots and those who see AI chatbots as less biased than other sources of information — but neither bring deep knowledge into their opinions.

In the search for unbiased information, interviewees are divided between those who worry about bias in AI chatbots and those who see AI chatbots as less biased than other sources of information.

This is an area where the lack of transparency and clarity about how AI chatbots work comes into play. At least one interviewee described AI chatbots as a “black box” and raised concerns that AI chatbots might covertly promote specific products without disclosing a financial interest. Others assumed they understood how they work but made claims that can’t be fully verified. Many Indian interviewees said they used AI chatbots to escape the “bias” of mainstream media, without fully acknowledging that the models underlying these chatbots are trained on content drawn largely from that very media. Two interviewees in the U.S. expressed similar perspectives, one saying that AI chatbots “don’t have an opinion” and thus cannot provide biased information, disregarding the potential for biases in training data or outputs. Some interviewees assume that because the AI chatbot linked multiple sources with different viewpoints, the generated results must represent a “neutral truth.” In trying to explain their judgments about bias, several interviewees reached the limits of their information. “Where does it get the information?” one wondered aloud. “I don’t know…” There’s no question that a synthesis across political standpoints would be valuable. What is difficult — perhaps even impossible — is determining whether AI chatbots can actually provide one.

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AI chatbots — such as ChatGPT, Grok, Amazon’s Alexa, Google AI Mode or the Washington Post’s “Ask the Post AI” — are software products which simulate human-like conversations and generate responses across a wide range of topics.

While even their creators caution against using them as arbiters of fact, research consistently demonstrates that people increasingly rely on them for information about the world. The line between “information” and “news” is hardly clear-cut. Information-seeking is also likely to include many topics where AI chatbot users might previously have turned to news sources.

We set out to learn from relatively early adopters in two countries (the U.S. and India) why and how they have incorporated AI chatbots into their information routines, and what this might mean for news providers.

Why we chose these two countries

• India and the U.S. represent the two largest markets for AI chatbots.
• Both India and the U.S. have highly concentrated news media ownership and increasingly politicized information habits.
• India is mobile-first in both behavior and infrastructure, while less than one in every five Americans rely primarily on smartphones for internet access.

• Overall, Americans express more negative attitudes towards AI than Indians do.

How we collected our data

Using the Respondent.io platform, the CNTI team recruited 27 adults in the U.S. and 26 in India. All of them participated in an hour-long virtual interview where they shared their screen and talked through their AI chatbot use and broader information habits.

Recruitment

To ensure that we were only speaking with regular users of AI chatbots, we excluded people who said they use AI chatbots less frequently than once a week.

To ensure that we were only speaking with people who pay attention to news information in the broadest sense, we excluded people who said they do not “keep informed about issues and events of the day” at least “somewhat closely.” In practice, most interviewees turn at least somewhat regularly to legacy news media sources, often via news aggregators and social media.

Beyond that, we took a maximum variation approach to a number of demographic variables within each country: age, gender, race and ethnicity, household income, educational attainment, location within the country and political ideology.

After we had completed about 18 interviews for each country, we conducted additional targeted recruitment to capture groups that were not well represented in our initial pool, specifically adults age 55 and older (both countries) and adults without a bachelor’s degree (U.S. only).

The full recruitment questionnaire and topline demographics of our interviewees are available here.

Thinkaloud protocol 

Concurrent thinkalouds ask people to narrate their behavior and answer questions about it in real-time. They are particularly valuable for understanding topics like information habits where self-reported data are unreliable. The goal of this study is to observe the needs and desires of the early adopters using AI chatbots to receive news.

Our research protocol included three semi-structured modules. During the first 10-15 minutes of the conversation, we asked broad questions about interviewees’ news repertoires and routines. We then turned to a screenshare and asked them to walk us through an AI chatbot query. For the last third of the interview, we asked interviewees to walk us through past AI chatbot queries, compare between the AI chatbots that they regularly use and provide more details about the other sources they turn to.

Researcher positionality

The researchers who designed the protocols, collected the data and analyzed the data are based in both the United States and India. CNTI’s small team cannot fully represent the diversity and breadth of these countries. In addition to relatively high educational status, our team as a whole has a high affinity for and knowledge about journalism. These attitudes may have colored our interactions with the interviewees.

The researcher who conducted all Indian interviews speaks both English and Hindi fluently and used both languages in interviews; all U.S. interviews were conducted in English.

How we analyzed our data

The research team created transcripts of interview audio, adding copious screenshots to clarify references in the text. After anonymization, transcripts were imported into Dedoose qualitative analysis software.

Two researchers conducted the bulk of the coding process, working separately on U.S. and India interviews, with a third researcher contributing to coding U.S. interviews. The codes were developed iteratively, with some codes informed by existing frameworks and others emergent in the data.

Transcription process 

Interviews were conducted with Google Meet, and Google Gemini produced a first transcript. Researchers reviewed each transcript for major errors prior to coding, and all quotations that appear in this report were reviewed by a researcher before publication.

Coding and follow-up analysis

The CNTI team’s initial coding schema focused on three different areas:

• Informational needs and how people meet those needs
• Interactions with AI chatbots
• Verification practices and concerns

The three areas correspond roughly to the three chapters of this report. We coded screenshots, text and anything else that fell within the thematic areas.

After all documents were coded, we reviewed all excerpts with the same code within each country to inductively identify further themes and patterns within each larger category. The researchers were in constant discussion about similarities and differences, and reviewed each chapter repeatedly.

This type of qualitative approach surfaces the breadth of experiences, but not the frequency of those experiences. In general, any theme that was shared by at least three interviewees in a single country appears in the report.

Informational needs 

The codes that fell under this category were informed by a set of reasons for seeking information identified by audience practitioners, also known as the “news user needs” framework. This framework categorizes the reasons that people access news content into four basic needs:

• People need to act and decide, and they need help.
• People need to know what’s going on.
• They need to understand what’s going on.
• People need stories that make them feel something, whether that’s outrage or joy.

Interactions with chatbots

Two initial codes fell into this category.

The first was a broad sequencing code that we used to identify both:

• extended interaction sequences with the AI chatbot, including repeated promptings or accepting suggested prompts and
• toggling between chatbots and other elements of interviewees’ news repertoires.

The second was for anthropomorphization, and included all actions or discussions where interviewees treated the AI chatbot as a human participant in interaction. This might include characterizations (e.g. “oh it’s my best friend”) as well as prompting strategies that treat it as human (e.g. including “please,” calling it “stupid” in a prompt).

Verification practices and concerns

We were interested in whether interviewees are concerned about the accuracy of the information they receive and how they approach verifying it.

Concerns we coded for included:

• Privacy and data protection
• Bias in both the AI chatbots and other news sources
• Delayed or outdated information being provided
• Broad questions about the information supply chain and how AI chatbots and other news sources verify (or don’t verify) their information

Verification practices and strategies we coded for (all AI chatbot-specific) included:

• Checking the list of sources and assuming those sources were reflected accurately
• Clicking through to external links and ensuring that those sources were reflected accurately
• Comparing the responses between two different AI chatbots
• Auditing AI chatbot responses by asking them known questions to assess performance before relying on them

We also included several other pathways. 

How we protected the research data

The AI chat window terminal is a deeply personal space and the researchers in this project are incredibly grateful to interviewees who opened this safe space to them. CNTI’s audio and video recordings and follow-up messages from interviewees contain a great deal of personal information.

All identifying information (including consent forms and video recordings of interviews) were saved on a password-protected, encrypted cloud drive that is only authorized to the core research team at CNTI. All interviews were conducted using our team’s videoconferencing software. Google Gemini was used to create first-draft transcripts; our team uses a workspace account that does not share data or use it for training purposes. Interviewees could opt out of automated transcription, although none did.

Moreover, transcripts and screenshots were anonymized to the extent possible before export for analysis in Dedoose. Information like names, specific locations and employment details were redacted, as were photos of individual faces. We present demographic information only in the aggregate (see topline) to prevent anyone from identifying individuals who participated in this research.

Ethical review

Research plans were reviewed and approved by TERC Institutional Review Board.

Consent forms were available in both English and Hindi, although no interviewees used the Hindi version of the form.

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Case Study 1: The skeptical power user

This interviewee represents the archetype of the ‘skeptical power user,’ one who distrusts traditional television news due to perceived bias but embraces the conversational power of AI chatbots. They turn to AI chatbots for all four kinds of information needs we have covered in this report: the need to act, the need to know, the need to understand and the need to feel.

News repertoire and sources: Synthesizing ideological balance

This interviewee’s news consumption is characterized by a rigorous pursuit of ideological balance and a rejection of sensationalism. They avoid Indian television news entirely, citing bias, and instead prioritize international news outlets like Al Jazeera and domestic English language print sources such as The Hindu and The Times of India. In their hierarchy of trust, written ground reports rank highest, followed by AI chatbots. While they access information via social media and YouTube, they rank YouTube videos last in terms of reliability, viewing them as prone to biased propaganda. When researching complex topics like the conflict in Gaza, they typically consume 10–12 articles and one to two videos from “both sides” to synthesize a neutral view, and hold “whole conversations with ChatGPT,” rather than relying on a single narrative.

AI chatbot usage and information needs: Controlled delegation

They delegate a wide array of tasks to AI chatbots, ranging from tracking daily macronutrients to debating sports statistics, yet retain ultimate authority by verifying the AI chatbot’s outputs against traditional news sources. Their relationship with AI technology is highly personalized. They nicknamed their preferred AI chatbot, ChatGPT, “Curler” (referencing FC Barcelona fans) and self-deprecatingly refer to themselves as “Burden” due to their relentless questioning. They instruct Curler to be “blunt” and “unbiased.”

AI chatbot preferences: “A conversation between two people”

They display a strong preference for ChatGPT over alternatives like Gemini, stemming largely from the former’s conversational fluidity. They feel ChatGPT’s answers are “easy” and feel “like a conversation between two people,” whereas they described Gemini’s outputs as “way too hard to respond” and “like AI AI.” Their comfort with ChatGPT extends to data sharing (e.g., name, birth year, family history), whereas they use Gemini only sporadically. 

Trust and verification: Trust, but verify 

While they find AI chatbots to be “mostly right,” they do not exhibit blind trust. Their workflow involves an iterative verification loop: searching a topic on ChatGPT, clicking linked sources to read full articles, then comparing the text against the AI chatbot’s summary to ensure accuracy. They retain ultimate authority, using the AI chatbot to distill information but relying on established news brands for ground truth.

They also acknowledge that the AI chatbot is sometimes wrong, occasionally failing to provide all the information found in the full linked article. When they notice the AI chatbot making a mistake, they correct it and instruct it to “double check” its data and learn from the error for future reference. 

This interviewee was interested in knowing more about the latest updates in the ongoing War in Gaza. They started off with a broad query and followed up with more specific questions on the hostage situation and Hamas’ statement. They found the links provided with every response very useful. Typically, they’d click on one of the links from established media outlets like Al Jazeera, The Times of India, the Wall Street Journal and CBS News and go through the articles. They employed a structured information pipeline: search, click on the AI chatbot sources, read the articles in their entirety and use the information to ask follow-up questions.

Case Study 2: The strategic snacker 

This interviewee represents a strategic ‘snacker’ of information. They exhibit a hybrid news consumption style that blends traditional print media with digital news sources and use AI chatbots to filter noise and curate a personalized news feed. 

News repertoire and sources: Editorials, op-eds and summaries

Their news repertoire is anchored by subscriptions to physical newspapers, specifically English language ones like The Hindu and The Indian Express and the Punjabi version of The Tribune. They value the tactile experience of reading physical papers, particularly the editorial and op-ed sections, which they use to improve their vocabulary and gain deeper knowledge. For scanning headlines and quick, daily updates, they rely heavily on Inshorts, a popular Indian news app that summarizes news stories from various sources into short, sixty-word bites. They also access news via social media and occasionally visit newspaper websites when away from home.

AI chatbot usage and information needs: A ‘wide net’ prompting strategy

To meet their information needs, the interviewee integrates AI chatbots like ChatGPT and Gemini into their routine, using them almost every day. Their primary motivations for using AI chatbots are time efficiency and the ability to summarize vast amounts of information quickly. They employ a ‘wide net’ prompting strategy, typically asking the AI chatbot to generate lists (see example). From these generated lists, they select specific stories of interest to dig deeper through follow-up requests for detailed summaries. They finalize this process by asking the AI chatbots to condense information such as dates and headlines into a concise paragraph to explicitly aid in memory retention.

AI chatbot preferences: ChatGPT, the Go-to App

They primarily use ChatGPT and Gemini on mobile, while occasionally using Claude and Perplexity on their laptop. They consider ChatGPT their go-to app, noting they have used it the longest, find it easy to use and subscribe to the paid version of the app. Notably, they prefer Gemini for its ‘deep research’ feature, which they utilize for academic projects and reports. They specifically value Gemini’s ability to produce organized outcomes, such as proper PDFs and flowcharts. In direct comparisons, they noted that Gemini often provides a better information hierarchy with useful sub-points, whereas ChatGPT sometimes offers better general overviews for broad topics.

Trust and verification: Diverse curation

The interviewee generally trusts AI chatbots to provide a balanced view by curating information from multiple sources, contrasting this with the singular perspective of a specific journalist. However, they remain skeptical in specific contexts. For instance, they expressed distrust toward Indian government data regarding politically contentious topics like climate change, preferring international sources instead. Furthermore, within their professional domain of law, they have detected inaccuracies where the AI chatbot fabricated facts about case laws, which led them to verify such data against books and Google searches.

This example shows the interviewee engaging in “snackable” consumption of news, prioritizing breadth over depth. Their interaction patterns are characterized by frequent requests for “Top 10 international news,” “Top 5 sports news” and similar short lists.

Indian user

Today news

ChatGPT

Today’s major headlines

1. India-US Trade Deal Nearing

India and United States are reportedly close to a trade agreement that would reduce U.S. tariffs on Indian imports to about 15-16% (down from much higher levels.

Why this matters:

• Lower tariffs can boost Indian exports to the US, helping Indian industries.

• For the U.S., It signals a potential shift in trade strategy with India.

[…]

Indian user

Give me today’s major in international news

ChatGPT

Here’s one major piece of international news today:

Kyiv, Ukraine: Russian Missiles & Drones Strike
• Overnight, Russian missile and drone attacks struck Kyiv and surrounding regions, killing six people (including two children) and causing widespread power outages across Ukraine.

[…]

Indian user

Can you give me a detailed summary about the Kyiv Ukraine conflict

ChatGPT

Absolutely – here’s a detailed, clear summary of the Kyiv-Ukraine conflict (Russia-Ukraine war) as of October 2025, covering its origins, timeline, key developments, and current status.

[…]

Indian user

Give me a paragraph with all important dates and headlines

ChatGPT

Here’s a compact paragraph summarizing the Russia-Ukraine conflict with all the major dates and key headlines:

The Russia-Ukraine conflict began in 2014, when Russia annexed Crimea and separatists seized parts of Donetsk and Luhansk…

When asked how they feel about the responses, the interviewee said,

I don’t think there are more than ten important news stories daily on a national level, so I think usually one or two or three are most important. So if there’s something that I have a little bit of interest in, then I’ll tell them that. ‘Give me a detailed summary of it,’ or ‘Give me a detailed version of it.’

Case Study 3: The perspective-seeker

This interviewee relies more heavily on AI chatbots for news than anyone else CNTI interviewed in the U.S. They regularly go to Gemini for a quick roundup of headlines, although they also value “quality time with news” when they need to learn about something with direct personal impact, like understanding the pros and cons of a local ballot proposition.

News repertoire and sources: Seeking out multiple ideological perspectives

This interviewee uses a broad repertoire of sources, including news outlet apps with regular push notifications, the social media feeds of friends and family members, conversations with coworkers and Google Gemini. They said they are concerned about bias, but are also particularly interested in getting news from multiple ideological perspectives. Following people they knew on social media means they can evaluate the slant based on what they knew about that other person. They also find it particularly important to get news that informs their individual actions. Specifically, they turn regularly to Gemini for round-ups of what was happening in their zip code and what topics will be on their ballot. 

U.S. user

What’s the latest headlines in [zip code]?

Gemini

The ZIP code [zip] covers the central and downtown area of [city].

Here are some of the latest headlines and recent local news:

Recent Crime & Public Safety:

• Double Murder Case: A man has been charged with the stabbing deaths of his wife and mother-in-law in [city].
• Retail Theft Ring Arrests: Three suspects were recently arrested in connection with a [city] retail theft ring.

[…]

U.S. user

What’s more info on retail theft ring arrests from last question?

Gemini

The organized retail theft ring arrests announced by Attorney General [name] in early 2024 involved a coordinated spree of burglaries that had a significant impact on [city] and the wider [region].

[…]

AI chatbot usage and information needs: staying “informed enough” and seeking “both sides”

For this interviewee, Gemini meets two primary needs. They use it for knowledge, as a way to scan local, national or global headlines and stay broadly familiar with what’s happening around them. “I don’t even know if I’m doing it correctly, but it seems to keep me informed enough,” they reflected. They also use it for context, specifically to understand a broad range of political perspectives. That kind of context is an area where they said they wanted more:

[I wish] there was an app that would give me both sides of the story and it was so unbiased that I knew I could trust it. If it was about the election, it would give me really strong Republicans views and really strong Democrats views and people right in between and then I could read all sides of the story and then I could make my own decision. So I don’t really know of something like that. It seems more like I need to take every source I get with a grain of salt and then form the opinion I want, hoping that I’m getting reliable sources.

AI chatbot preferences: “ChatGPT just doesn’t give you that detail”

Like many other interviewees, this person has a strong preference for one AI chatbot over others. For them, it is Gemini. They had been an early tester of Bard, and “at first, I was like, ‘this is so much work for so little money.’ But then […] I just started getting, ‘wow, this is so much better than Yahoo! or just Googling news.’ You get so much more than just a search engine.” Like others, their preference has grown over time: they found it easy to use from the get-go, have invested time with it and have gotten to a place where it provides information in a format they are used to and comfortable with. Even so, they observed that Gemini is still “not ideal” because it can’t fully anticipate their needs. “It doesn’t know my personality. Gemini doesn’t know that the person that works here has been talking to me so much about a certain proposition and that is particularly important to me. Gemini is not living with me. So I don’t always get what I’m looking for.” 

Trust & verification: “It’s fact-based as opposed to having a lot of opinions or interpretations”

They said they find Gemini more factual than many news sources, and take confidence from the fact that they could look up whether the responses are true. They almost never do so, however. As they described it, “I can literally just say, ‘what’s the biggest headlines in [zip code]?’ and they’ll be listed and I feel like it’s pretty unbiased, unlike certain news channels. You kind of can get both sides of the story and then it also does really good summaries. So instead of getting a humongous article I can also say, ‘can you summarize what you just said?’” Getting short summaries is especially helpful when there’s an overwhelming amount to keep up with.

Case Study 4: The cautious optimist

This interviewee epitomizes “trust but verify” optimism towards AI chatbots. They consider them a “concierge for information” even as they cautioned that they are an “80/20 source.”

News repertoire and sources: Google News “seems to learn my interests”

This interviewee uses Google News as their most important news feed because it serves them information from a range of sources on topics they care about. In fact, their browser homepage is set to Google News. They also pay for a New York Times subscription and two local news outlets in their former hometown, primarily to follow local sports. They’re in a community Facebook group for hyperlocal information, they also watch some TV and they use both ChatGPT and Google AI mode for sports content.

AI chatbot usage and information needs: ChatGPT helps them accomplish things

They use AI chatbots for a range of information needs, most of which fall solidly under ‘acting.’ They showed us their history: in the last few days before their interview, they had asked ChatGPT to calculate their protein intake, to identify the sports programming on a particular channel and to collate reviews of a particular brain health app. During our call, they also asked for advice on a planned home renovation. They even credited ChatGPT with a newfound awareness of the breadth of their hobbies, because ChatGPT makes it easy for them to plan. When they are looking for up-to-date knowledge and understanding, on the other hand, they generally start with Google News.

At one point during the interview, they used Google search (in AI mode) to search for a story that was paywalled. They were hoping to find something they could access on the same topic, but ultimately got the information from an AI chatbot summary instead.

AI chatbot preferences: locked into ChatGPT by virtue of habit and history

This interviewee uses ChatGPT more frequently than other AI chatbots and they explained that this preference was largely due to the time and energy they had already invested. “I use ChatGPT preferentially over Google Gemini, it’s just become a habit. I’ve got history out there. I can go retrieve things. I’m prolific on ChatGPT, plus I have a short-term memory. Always have. And so having this history back there to go search on, it’s like Amazon, you get hooked and you got subscriptions and pretty soon you’re just going back to the same source for things.” At the same time, they trust Google’s AI Mode much more because they find it less willing to speculate: “I haven’t caught Google AI lying to me yet and Chad [sic] has lied to me over and over again with the best of intentions, with the confidence. He reminds me of a neighbor here who lied to me all the time and […] I’m not saying I think of [ChatGPT] as a pathological liar. But I think of ChatGPT as confidently giving me information that I know at times it’s like ‘you’re so wrong.’” They also see AI Mode as enhancing something they were already doing, which they valued. They feel like Google has successfully replaced“links to information so you can go research yourself and figure it out” with“the crib notes, the executive summary.”

Trust & verification: moving beyond “garbage in, garbage out”

It is not uncommon for this interviewee to identify a problem with the responses they receive from ChatGPT based on their own prior knowledge or a topic. In fact, they raised repeated concerns about “garbage in, garbage out.” Interestingly, they were most concerned with the quality of their own prompts and seemed less aware of the quality of information used in training or referenced in the actual reply. To the extent that they raised concerns about inputs beyond their prompt, they focused their frustration on how ChatGPT doesn’t always reference the most recent sources: “It’s hard to give any AI a 10 [on a trust scale] because I’ve learned that, again, ‘garbage in, garbage out.’ Sometimes it’s me thinking I’ve communicated clearly. But also sometimes it’s just, there’s a time lapse.”

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When I examined my interviewees’ responses to my inquiries about journalism’s technological future, it became clear that this shift toward higher volume production with limited staff pushes journalists to focus on the present and immediate future of news, leaving most journalists with little energy to consider long-term changes. This profound shift in the industry means the majority of daily news journalists cannot imagine more distant technological futures. This separates journalists from the discourse on long-term impacts of cutting-edge technology tools like artificial intelligence (AI). To safely move forward with AI and other emerging technologies in the newsroom, it is essential to enable daily news journalists to participate in imagining what the future relationship between journalism and AI might be.

What is the current relationship between journalism and AI?

Current uses of AI in news among my interviewees and others varies widely; it is used to create SEO-friendly headlines, summarize articles for social media, write and debug code, process documents with Optical Character Recognition (OCR), transcribe audio files and more. Each of these uses meets an immediate need in the newsroom: they contribute to attempts to streamline workflows, increase efficiency and expand coverage, often in hopes of increasing revenue.

These applications also primarily use out-of-the-box tools from technology companies like OpenAI, not open-source or bespoke tools created by and for journalists, though there are limited examples of this, from Rolli to track misinformation to Llamafile to use as a locally-run LLM. None of these applications fundamentally changes how audiences interact with news or substantially reimagines news workflows. Instead, journalists slot AI in as an aide or assistant.

What futures do journalists envision now?

I asked journalists, news leaders, journalism academics and journalism advocates, “If you could envision the ideal future for the relationship between journalism and AI tools, what would that look like?” The vast majority of interviewees jumped straight to making their current uses better — more accurate transcription, more reliable OCR, summaries without hallucination and so on. Many also mentioned their hopes for increased privacy and security with AI tools.

A small portion of interviewees noted that they don’t want AI and journalism to have a relationship at all. In these journalists’ minds, the cost — financial, social and environmental — of using AI tools is not worth small additions to efficiency or revenue.

Only a few interviewees had a vision that went beyond iterative improvement. Most of them were in leadership or product roles, not daily reporting. These ideas included offering individualized homepages curated by AI, so subscribers can see their most relevant stories first; a new technology development organization made for and by journalists that creates AI tools optimized for investigative work; and AI chatbots on news sites that can answer questions about current events based solely on coverage by that news organization, which have become a reality since I began interviews.

Daily journalists’ focus on iterative improvements to existing AI uses is indicative of a deeper trend towards short-term wins in newsrooms. Yet, the long-term health of the news industry will rely on journalists taking charge of technological futures, and of emerging tools themselves. The constant churn of daily news stunts imaginative technological futuring and leads newsrooms to rely on tools made and controlled by technology companies, stripping journalists of their future professional agency to decide what tools they use, who receives their data and, potentially, what stories they tell. If journalists use directive tools, like AI chatbots that suggest how to move forward with a task, without knowing how the tools generate a directive or what biases they have, then a level of uncertainty is imbued into the journalistic process — and while AI tools cannot be held accountable for this uncertainty, the journalists using them can be.

How can the news industry better facilitate long-term technological futuring?

If enabling journalists to imagine what journalism could look like in the distant future will make journalism more responsive, sustainable, and innovative, then action should be taken now to enable that. One way to do so is for newsroom leaders, news product developers and news strategists to make time for daily news journalists to step out of the constant deluge of news to think about the future, whether through office hours, surveys or communal brainstorming. These conversations might begin like my interviews did — with short-term issues — but journalists will rise to the challenge of thinking outside the box.

There is no silver bullet to understanding how journalism and emerging technology, like AI, will interact in the coming decades, but proactive futuring now could go a long way in putting journalism in the driver’s seat.

Emilia Ruzicka is a data journalist, researcher and editor. They recently graduated with their MA in media, culture, and technology from the University of Virginia. More information about Emilia and their work can be found at emiliaruzicka.com.

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— Craig Forman, Executive Chair, CNTI

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— Amy Mitchell, Executive Director, CNTI

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— Amy Mitchell, Executive Director, CNTI

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