AI Research
How US adults are using AI, according to AP-NORC polling
Most U.S. adults say they use artificial intelligence to search for information, but fewer are using it for work, drafting email or shopping.
Younger adults are most likely to be leaning into AI, with many using it for brainstorming and work tasks.
The new findings from an Associated Press-NORC Center for Public Affairs Research poll show that 60% of Americans overall — and 74% of those under 30 — use AI to find information at least some of the time.
The poll highlights the ubiquity of AI in some areas — as well as its limits in others. Only about 4 in 10 Americans say they have used AI for work tasks or coming up with ideas, a sign that the tech industry’s promises of highly productive AI assistants still haven’t touched most livelihoods after years of promotion and investment.
At the same time, wider AI adoption by younger Americans shows that could change.
There’s a particularly large age divide on brainstorming: About 6 in 10 adults under age 30 have used AI for coming up with ideas, compared with only 2 in 10 of those age 60 or older. Young adults are also more likely to use AI to come up with ideas at least “daily.”
Young adults are most likely to use AI
Bridging the generations are people like Courtney Thayer, 34, who’s embracing AI in some parts of her life and avoiding it in others.
Thayer said she is regularly using ChatGPT to come up with ideas about planning what to eat, while also having it calculate the nutritional value of the pumpkin-banana-oat bread she’s been baking for years.
“I asked it to make a meal prep for the week, then to add an Asian flair,” said Thayer, of Des Moines, Iowa. “It wasn’t the most flavorful thing I’ve ever had in my life, but it’s a nice stepping off point. More importantly, I use it for the amount so that I’m not over-serving myself and ending up with wasted food.”
The audiologist has embraced AI at work, too, in part because AI technology is imbued in the hearing aids she recommends to patients but also because it makes it easier and faster to draft professional emails.
She avoids it for important information, particularly medical advice, after witnessing chatbots “hallucinate” false information about topics she spent years studying.
Roughly 4 in 10 Americans say they use AI for work tasks at least sometimes, while about one-third say they use it for helping to write emails, create or edit images, or for entertainment, according to the poll. About one-quarter say they use it to shop.
Younger adults are more likely than older ones to say they have used artificial intelligence to help with various tasks, the poll shows.
Searching for information is AI’s most common use
Of the eight options offered in the poll questions, searching for information is the most common way Americans have interacted with AI. And even that may be an undercount, since it’s not always apparent how AI is surfacing what information people see online.
For more than a year, the dominant search engine, Google, has automatically provided AI-generated responses that attempt to answer a person’s search query, appearing at the top of results.
Perhaps defying emerging media consumption trends, 28-year-old Sanaa Wilson usually skips right past those AI-generated summaries.
“It has to be a basic question like, ‘What day does Christmas land on in 2025?’” said the Los Angeles-area resident. “I’ll be like, ‘That makes sense. I trust it.’ But when it gets to specific news, related to what’s happening in California or what’s happening to the education system and stuff like that, I will scroll down a little bit further.”
Wilson, a freelance data scientist, does use AI heavily at work to help with coding, which she said has saved her hundreds of dollars she would have had to pay for training. She also occasionally uses it to come up with work-related ideas, an attempt to bring back a little of the collaborative brainstorming experience she remembers from college life but doesn’t have now.
When it first came out, Wilson said she also used ChatGPT to help write emails, until she learned more about its environmental impact and the possibility it would erode her own writing and thinking skills over time.
“It’s just an email. I can work it out,” she said. “However many minutes it takes, or seconds it takes, I can still type it myself.”
Most don’t use AI for companionship — but it’s more common for young adults
The least common of the eight AI uses was AI companionship, though even that showed an age divide.
Just under 2 in 10 of all adults and about a quarter of those under 30 say they’ve used AI for companionship.
Wilson has no interest in AI companions, though she isn’t surprised that others do because of the effect of the COVID-19 pandemic on her generation’s social experiences.
“I totally understand and sympathize behind why people in my age group are leveraging it in that way,” Wilson said.
Thayer, the audiologist, also has no interest in AI companionship, though she tries to be polite with chatbots, just in case they’re keeping track.
“I mean, I am nice to it, just because I’ve watched movies, right?” Thayer said, laughing. “So I’ll say, ‘Can you make me a meal plan, please?’ And, ‘Can you modify this, please?’ And then I’ll say, ‘Thank you.’”
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The AP-NORC poll of 1,437 adults was conducted July 10-14, using a sample drawn from NORC’s probability-based AmeriSpeak Panel, which is designed to be representative of the U.S. population. The margin of sampling error for adults overall is plus or minus 3.6 percentage points.
A new global reviewer survey from IOP Publishing (IOPP) reveals a growing divide in attitudes among reviewers in the physical sciences regarding the use of generative AI in peer review. The study follows a similar survey conducted last year showing that while some researchers are beginning to embrace AI tools, others remain concerned about the potential negative impact, particularly when AI is used to assess their own work.
Currently, IOPP does not allow the use of AI in peer review as generative models cannot meet the ethical, legal, and scholarly standards required. However, there is growing recognition of AI’s potential to support, rather than replace, the peer review process.
Key Findings:
- 41% of respondents now believe generative AI will have a positive impact on peer review (up 12% from 2024), while 37% see it as negative (up 2%). Only 22% are neutral or unsure—down from 36% last year—indicating growing polarisation in views.
- 32% of researchers have already used AI tools to support them with their reviews.
- 57% would be unhappy if a reviewer used generative AI to write a peer review report on a manuscript they had co-authored and 42% would be unhappy if AI were used to augment a peer review report.
- 42% believe they could accurately detect an AI-written peer review report on a manuscript they had co-authored.
Women tend to feel less positive about the potential of AI compared with men, suggesting a gendered difference in the usefulness of AI in peer review. Meanwhile, more junior researchers appear more optimistic about the benefits of AI, compared to their more senior colleagues who express greater scepticism.
When it comes to reviewer behaviour and expectations, 32% of respondents reported using AI tools to support them during the peer review process in some form. Notably, over half (53%) of those using AI said they apply it in more than one way. The most common use (21%) was for editing grammar and improving the flow of text and 13% said they use AI tools to summarise or digest articles under review, raising serious concerns around confidentiality and data privacy. A small minority (2%) admitted to uploading entire manuscripts into AI chatbots asking it to generate a review on their behalf.
Interestingly, 42% of researchers believe they could accurately detect an AI-written peer review report on a manuscript they had co-authored.
“These findings highlight the need for clearer community standards and transparency around the use of generative AI in scholarly publishing. As the technology continues to evolve, so too must the frameworks that support ethical and trustworthy peer review”, said Laura Feetham-Walker, Reviewer Engagement Manager at IOP Publishing and lead author of the study.
“One potential solution is to develop AI tools that are integrated directly into peer review systems, offering support to reviewers and editors without compromising security or research integrity. These tools should be designed to support, rather than replace, human judgment. If implemented effectively, such tools would not only address ethical concerns but also mitigate risks around confidentiality and data privacy; particularly the issue of reviewers uploading manuscripts to third-party generative AI platforms,” adds Feetham-Walker.
Pascal AI Labs, a rapidly growing technology company focused on transforming how investment research is conducted, has announced the close of a $3.1 million seed funding round. The funding was led by Kalaari Capital, with additional participation from Norwest, Infoedge Ventures, Antler, and several prominent angel investors.
This funding marks a significant step in the company’s journey to bring advanced, AI-driven research capabilities to financial institutions worldwide.
The new capital will be used to speed up the development of Pascal AI’s autonomous investment workflows, expand its presence in the United States, and form strategic partnerships with key data providers.
The company’s platform is already in use by more than 25 financial firms across the U.S. and the Asia-Pacific region, including private equity funds managing $2 billion in assets and one of the world’s top three asset managers with over $1 trillion under management.
Pascal AI offers secure and native connections to data on over 16,000 publicly traded companies across 27 markets, giving investment teams a broad and reliable foundation for their work.
The problem that Pascal AI is addressing is one that many investment professionals are familiar with. Analysts and portfolio managers are inundated with vast amounts of data from company filings, earnings call transcripts, market reports, and internal research notes.
While existing platforms can surface this information, they often fail to capture the accumulated judgment and institutional knowledge that experienced investors rely on. As a result, analysts spend hours manually piecing together information, and chief investment officers often lack a clear, forward-looking view of their portfolios.
Pascal AI takes a different approach by automating the entire investment lifecycle. The platform learns from a firm’s proprietary history—its past decisions, research notes, and investment patterns so it can reason and act like a seasoned investor rather than simply retrieving data. This means it can proactively connect insights, identify risks, and suggest actions in a way that reflects the unique thinking of each firm.
Because the stakes in investment decision-making are high, trust and security are central to Pascal AI’s design. The platform is built on a proprietary Knowledge Graph that makes every action fully auditable and traceable. It supports enterprise-grade security features, including role-based permissions and the option for on-premise deployment, ensuring that sensitive information remains protected while still enabling robust AI-driven analysis.
Pascal AI was founded by Vibhav Viswanathan and Mithun Madhusudan, both of whom bring deep expertise in finance, artificial intelligence, and scaling technology products.
Viswanathan, a graduate of the University of Chicago Booth School of Business, previously led AWS Inferentia and Neuron in Silicon Valley and has hands-on investment experience from his time at Capital Group and NEA-IUVP.
Madhusudan, an alumnus of the Indian Institute of Management Bangalore, has led AI and product teams at Indian tech unicorns Apna and ShareChat, where he helped scale AI products to more than 100 million users.
KEY QUOTES:
“The future of investment management is autonomous investment research. Pascal AI is systematically automating complex investment workflows with the long-term vision of creating a fully autonomous investment research company. This funding allows us to accelerate that journey, moving from workflow automation to true autonomy, and giving analysts instant, auditable insights and CIOs a continuously updated view of exposures and performance”.
Vibhav Viswanathan, co-founder and CEO of Pascal AI
“At Kalaari, we believe the next decade will see a decisive shift toward autonomous research platforms that can scale human judgment with machine intelligence. Pascal AI is at the forefront of this transformation—building secure, auditable, and truly agentic workflows that don’t just process information, but reason like an investor. What stood out to us was the clarity and conviction with which Vibhav and Mithun are reimagining how investors and CIOs make decisions. With strong early traction from marquee global clients, the team has already validated the depth of the problem and the strength of their solution. We are excited to partner with them on this mission.”
Kalaari Capital Partner Sampath P
With all of the challenges facing health care — a shrinking workforce population, reduced funding, new technologies and pharmaceuticals — it’s no longer an option to change, but an imperative. In order to keep caring for our communities well into the future, we need to transform how we provide care to people. Technology, artificial intelligence and digital transformation can not only help us mitigate these trends but truly innovate and find new ways of making health better.
There are many exciting capabilities already making their way into our field. Ambient listening technology for providers and other automation and AI reduce administrative burden and free up people and resources to improve front-line care. Within the next five years, we expect hospital “smart rooms” to be the norm; they leverage cameras and AI-assisted alerting to improve safety, enable virtual care models across our footprint and allow us to boost efficiency while also improving quality and outcomes.
It’s easy to get caught up in shiny new tools or cutting-edge treatments, but often the most impactful innovations are smaller — adapting or designing our systems and processes to empower our teams to do what they do best.
That’s exactly what a new collaboration with the AHA and Epic is aiming to do. A set of point-of-care tools in the electronic health record is helping providers prevent, detect and treat postpartum hemorrhage, which is responsible for 11% of maternal deaths in the U.S. Early detection and treatment of PPH is key to a full recovery. One small innovation — incorporating tools into your EHR and labor and delivery workflows — is having a big impact: enhancing providers’ ability to effectively diagnose and treat PPH.
It’s critical to leverage technology advancements like this to navigate today’s challenging environment and advance health care into the future. However, at the same time, we also need to focus on how these opportunities can deliver measurable value to our patients, members and the communities we serve.
I will be speaking with Jackie Gerhart, M.D., chief medical officer at Epic, later this month for a Leadership Dialogue conversation. Listen in to learn more about how AI and other technological innovations can better serve patients and make actions more efficient for care providers.
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