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Sam Altman: The alchemist of AI

As OpenAI CEO, Sam Altman unleashed ChatGPT, creating a $500 billion behemoth. As a new father, he's building a future his kids—and the rest of us—will have to live in

Last Updated: Mar 26, 2026, 15:39 IST18 min
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OpenAI CEO Sam Altman. Photo by Cody Pickens for Forbes
OpenAI CEO Sam Altman. Photo by Cody Pickens for Forbes
In a Nutshell
RAPID READ
  • Altman aims to build the $830B foundation of the future AI economy
  • OpenAI is branching into hardware, chips, and Disney media deals
  • Critics weigh his ambitious AGI goals against risks and corporate "chaos"

Sam Altman says the stick of uranium in his office is nothing to worry about. Sitting vertically on his desk at OpenAI headquarters in San Francisco, it is perhaps the most eyebrow-raising of the impressive array of historic innovations he has collected over the years. “That’s depleted,” he says casually of the uranium-238 rod, the same element used to create nuclear energy. “It’s not going to hurt you.” He waves a Geiger counter over it and proves his point.

“You make a big discovery in physics and… unlock basically unlimited energy,” he says of the uranium rod. “We didn’t know about this, then theorised that such a thing was possible. A couple of decades later, they had made an atomic bomb. Just a crazy, fast thing.”

Altman, wearing Adidas Lego Ultraboost sneakers and a simple grey knit sweater, works methodically and chronologically through the artefacts, most of which typically live in his home office, unseen by anyone but his closest friends. On display today, Altman says: A 40,000-year-old hand axe (“an amazing, general-purpose Stone Age tool”), a 3,500-year-old bronze sword (“an interesting example of technology having a big geopolitical impact”) and a compressor fan blade from a Concorde jet engine (“the only piece small enough” to carry in). In casual defiance of museum curator protocol, he has lugged all these items to his office in a duffel bag, individually wrapped in bathroom towels.

“I am consistently amazed by how much each generation builds a new layer of scaffolding,” he says of technological progress. “We’re really seeing that now.”

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As memorable as the uranium rod is, one of the other striking items in Altman’s collection is an old GPU chip. It trained an early version of the model behind OpenAI’s signature product, ChatGPT, which catapulted AI into the mainstream in November 2022 and set off a chain reaction of innovation that may turn out to be as transformative as the Industrial Revolution.

America has a storied history of innovators who aren’t known for inventing, whose achievement instead was pushing the cutting edge into daily life by sheer force of will and wits. Think Steve Jobs, Bill Gates and Elon Musk. Thomas Edison didn’t invent the light bulb. He—or rather his team—improved it with a longer lasting filament and then aggressively brought it to market.

Altman is of that mould. He’s an investor and an accelerator more than an engineer or a scientist. His vision isn’t about perfecting consumer products—it’s about building the underlying systems that the rest of the economy may soon depend on. ChatGPT now has more than 800 million weekly users. OpenAI, with more than $13 billion in revenue last year, was recently valued at $500 billion and is reportedly seeking an additional $100 billion investment, which would raise its value to $830 billion (Altman has no direct equity stake in the company, but his other investments make him worth an estimated $3 billion). Inspired by OpenAI, big tech could pour an estimated $500 billion into AI data centres and chips this year. At this moment, it is perhaps the most important company in the world.

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That has made Altman, now 40, the subject of a fast-growing hagiography. Bob Iger, who is stepping down as Disney CEO in March, says Altman can “look around corners” to see the future. Airbnb co-founder Brian Chesky calls him “one of the two most ambitious people I know” (the other being Musk). Apple design legend Jony Ive says enigmatically that Altman “is comfortable with the unknown, but he is not casual about the responsibility”. Renowned VC Paul Graham (Altman’s former mentor at the startup incubator Y Combinator) offers a balder take: “He’s good at convincing people of things. He’s good at getting people to do what he wants.”

Though soft-spoken with a low-key Midwestern demeanour, Altman is something of an AI carnival barker. His aggressive predictions about the technology’s exponential growth need to come true to justify not just OpenAI’s valuation but the vast economic and social bets forming around it. And it’s not clear he quite knows how to get there. Can he deliver on a future as big and fast and expensive as the one he describes?

Forbes has been tracking Altman for more than a decade. In 2015, he was a featured member of the inaugural Forbes 30 Under 30 Venture Capital list as the newly minted 29-year-old leader of Y Combinator. “It’s cool that you can make a list of the problems in the world and then fund companies to solve them,” he told us.

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Viewed solely through the lens of those investments, Altman is a wildly ambitious business leader, meticulously architecting his vision of the future. As the mobile era solidified in the 2010s, Altman presciently backed an array of companies—investing $15,000 for 2 percent of San Francisco- and Dublin-headquartered payments giant Stripe before it even had a name, and leading a $50 million funding round into social media platform Reddit in 2014, for example—that grew into mainstays of the app economy.

With AI he’s doing it again. There’s OpenAI, of course. But there’s also Washington-based Helion Energy, which is attempting to harness the nearly limitless power of nuclear fusion (the type of energy the sun uses), and California’s Oklo, which is developing more conventional nuclear fission reactors, but ones that are smaller and more modular. Both could serve AI’s energy-guzzling needs. Then there’s San Francisco-based World (formerly Worldcoin), which is developing tech to provide “proof of humanness” in an emerging world of AI deepfakes. There’s also the nascent Merge Labs, working on neural computing in the San Francisco Bay area. And through a non-profit called OpenResearch, Altman backed one of America’s largest experiments on universal basic income—an effort that would provide all citizens with a small, guaranteed, no-strings-attached wage as a possible remedy for the economic disruption AI may cause.

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“I think I am unusually good at projecting multiple things—years or a couple of decades into the future—and understanding how those are going to interact together,” says Altman. Some people are good at predicting what’s next. Others see how different worlds are about to overlap. “But the combination of them is kind of my thing,” he says.

These days Altman has a new lens through which to view the promise and perils of AI: Fatherhood. He and his husband have a baby son and are expecting their second child later this year.

Altman’s Rolodex is a who’s-who of Silicon Valley power players. Japanese tech conglomerate SotfBank has poured billions into OpenAI and announced a joint venture to bring AI to industries across Japan. SoftBank founder Masayoshi Son (right) says Altman thinks in decades. Photo by Getty Images

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“People say, ‘Oh, I’m glad you have a kid because now you won’t do something to destroy the world’, ” Altman says. “I was really set on not doing that before. Didn’t need the kid.”

Altman’s Backstory is well-told: Raised in St Louis, Missouri, a world away from Silicon Valley, he was a nerd fascina­ted by science, energy and artificial intelligence. “I’ve been obsessed with the same couple of ideas my whole life,” he says. They haven’t changed “since I was like 18”.

Altman landed at Stanford University in 2003, intent on studying AI at a time when the zeitgeist was more Web 2.0. During his sophomore year, he won a business-plan competition for what would eventually become his first startup, Loopt, a phone app for sharing your location with friends. That’s when he first heard about Y Combinator. He took the red-eye flight to Boston to interview with founder Graham. “I remember thinking, this is what Bill Gates must’ve been like,” Graham recalls of their first meeting.

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Graham was so impressed that when he stepped back in 2014, he tapped Altman, then only 28, to run the place. The reason? “Sam gets what he wants,” Graham says. “So if the only way Sam could succeed in life was by YC succeeding, then YC would succeed.”

Altman played in a variety of sandboxes at Y Combinator but became very fond of one side project in particular: An AI research outfit named OpenAI. Founded in 2015 as a non-profit, OpenAI was striving to create AGI, or artificial general intelligence, basically AI that can “think” like humans. Altman personally recruited Greg Brockman, then CTO of Stripe, and famed AI researcher Ilya Sutskever, known for his pioneering work in neural networks, to join as co-founders—and helped convince Musk, then one of his personal heroes, to back it with $38 million. Altman’s focus on Open­AI soon became almost monomaniacal, making Y Combinator more of a fading hobby than the calling Graham had intended it to be. In 2019, Graham and Y Combinator co-founder Jessica Living­ston were stunned to read a press release announcing Altman as CEO of a new for-profit branch of OpenAI. Livingston asked him to recommit to Y Combinator or step down.

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There is “some deserved flak there”, Altman says now. “When it was clear to me that OpenAI was going to work and I was running both things, I was just like, ‘I can pretend that I still care as much about YC, but [OpenAI] is my purpose and I need to go do it’.”

This wouldn’t be the first time Altman’s priorities would run afoul of his colleagues. Days before the Thanksgiving holiday in 2023, he was fired by OpenAI’s non-profit board for not being “consistently candid”. Leading the coup was co-founder Sutskever, who’d told the board that “Sam exhibits a consistent pattern of lying” and accused him of “creating chaos, starting lots of new projects and pitting people against each other” in pursuit of his goals. Altman would be reinstated just five days later after what was arguably the most farcical corporate drama in Silicon Valley history—a saga that saw OpenAI employees revolting and threatening to quit en masse if Altman wasn’t reinstalled, Microsoft suddenly stepping in to hire him, and rumours of a new AI model so powerful that it frightened those who saw it.

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All this occurred amid a dizzying swirl of allegations of duplicity and recklessness. A board investigation would later conclude that Altman was indeed the right leader for OpenAI, but the incident left an indelible mark on his reputation.

It didn’t help that three years prior, an internal power struggle had seen a faction of top OpenAI employees, including siblings Dario and Daniela Amodei, split off from the company to found Anthropic, a rival that touts a particular focus on AI safety. Now valued at around $350 billion, with some $4.5 billion in 2025 revenue, it has become one of OpenAI’s most formidable rivals.

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Even more combustible than the Anthropic defection was OpenAI’s decision to restructure the organisation to add a for-profit arm. The move allowed OpenAI to function more like a typical company and take funding from investors, including a key $13 billion investment from Microsoft beginning in 2019. Musk was vehemently opposed and left in protest, receiving no equity in the for-profit entity. Palace intrigue abounds, but in a lawsuit, Musk claims he left because OpenAI abandoned its original mission to create AI to benefit humanity in favour of maximising profits. OpenAI maintains that he instead left because the company wasn’t giving him control of the for-profit. Musk turned around and launched competitor xAI in 2023; in early February, he confirmed the merger of xAI and his SpaceX rocket and satellite maker, creating a company with an estimated value of $1 trillion. The case is expected to go to trial in the first half of this year. “It’s not how I would choose to spend however many days it’s going to take. But I feel good about our position,” Altman says.

While Altman felt the creation of a for-profit was necessary for OpenAI to thrive, there’s no question it benefited him as well. It bolstered his influence and his power—though, perplexingly to critics, not his wealth. Altman had no direct stake in OpenAI when it was founded and still doesn’t, even though he could have taken one in the restructuring. Why? “I don’t know. I don’t have a great answer,” he says. “Probably I should [take one], just so I never have to answer that question.” He adds that his lack of equity “is this super-confusing, insane conspiracy-theory-producing thing”.

The restructuring has made a bitter enemy of former Altman hero Musk, who used xAI to build a ChatGPT competitor called Grok. Billed as a “truth-seeking” AI model, it is mired in an endless swamp of controversy for repeating false narratives about white genocide, calling itself “MechaHitler” and apparently generating sexualised pictures of minors (the company later apologised). “I wish they would do things differently. It’s crazy to me how much time he spends attacking us,” says Altman, complaining about Musk’s accusations that OpenAI doesn’t act safely. “Their own house is on fire on these things consistently.”

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While Altman’s tendency to race ahead with ideas that excite him has gotten him into trouble, it’s also a tentpole of his success. Take the launch of ChatGPT. In 2022, OpenAI’s leadership had wavered on releasing the model to the public, arguing it was better to wait for a more powerful one. It was Altman who convinced them to go when they did. “Sam was like, ‘Let’s just try to get this out’, ” says Brockman, OpenAI’s co-founder and presi­dent. The night before the launch, he recalls the team making predictions on how it would go. “I thought it would be a little bit of a flash in a pan,” he says now. “Sam always had the conviction.”

As OpenAI’s valuation and forecasts for the size of the AI market attest, the timing of that launch couldn’t have been better. He’s “forward-thinking in the extreme”, Disney’s Iger says of Altman. “Combining both patience and impatience.”

There’s something else at work here, too: Altman knows his history. His itch to release products quickly is informed by studying Xerox PARC, the legendary Silicon Valley research lab known for inventing the modern graphical user interface, laser printers and computer mouse, yet failing to commercialise any of them. “You have to have an economic engine in the cycle,” Altman says. “I think there’s probably a lot of great innovation that has never gotten out of the lab because someone didn’t do the work to just get it into people’s hands.”

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That’s something he’s working on now. ChatGPT’s rudimentary text interface dates back to Eliza, a 60s-era chatbot that famously, and badly, impersonated a psychotherapist. Altman wants to invent a new paradigm entirely, devi­ces to make AI essential to our daily lives.

To that end, OpenAI bought IO, the hardware firm of Ive (the designer of the iMac, iPhone and Apple Watch), for $6.5 billion in July. “Sam understands that user interface is not decoration,” Ive says. “It defines the human experience.”

Altman is enraptured by the project, but intractable in his refusal to describe it; the team works in a secret office in San Francisco. He sees a family of gadgets that provide “extreme contextual awareness and proactive assistance”. There might be a “little friendly companion” that observes you, helpfully expediting tasks and generally improving your daily experience. At one point he describes a device that would have chosen the perfect selection of artefacts he had shown off earlier. It would say, “‘I know what Sam has been thinking about recently, what he’s likely excited about’,” he says. “‘I’ve also watched where his eyes go in the room’.”

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This could all be misdirection. Altman has a reputation for shiny object syndrome. And the challenge of conceiving the devices that could help define human experience is not without risk. Sili­con Valley is littered with “world changing” failures—the Segway scooter, Magic Leap’s ferociously overpromised augmented reality and more recently, Humane’s silly wearable AI assistant pin (an Altman-backed company). “It may flop,” Altman concedes. “Not many times in history have people figured out a fundamentally new compu­ting interface.”

It also could be harmful. OpenAI has been criticised for releasing products without proper safety testing and for shipping features that prioritise engagement over psychological well-being. It has been named in several wrongful death suits that allege ChatGPT directly encouraged and/or facilitated self-harm and suicide. Many argue the behemoth data centres that undergird ChatGPT are power-gorging, water-sucking environmental nightmares. Open­AI has always been quick with apologies and pledges to do better, but it’s hard not to see a pattern emerging.

In December, Altman and Iger spun heads in Silicon Valley and Hollywood when they announced a deal to let OpenAI license characters from the Disney universe, including Mickey Mouse, Darth Vader and Cinderella, to be used in OpenAI’s Sora app, which uses AI to generate realistic videos from the simplest prompts. It was a stunning alliance, as Disney is notoriously protective of its intellectual property, and Hollywood has generally viewed AI as an existential threat. Discussed for more than a year, the agreement allows Disney, among other things, to include Sora-generated videos on its Disney+ streaming service. It also saw Altman convince the entertainment giant to make a $1 billion equity investment in OpenAI, giving the AI behemoth the most magical of Hollywood blessings. “Sam wanted that as a sign of both confidence and, essentially, to bolster the partnership,” Iger says. “And to create a situation where Disney had a little bit more skin in the game.”

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It also speaks to Altman’s influence, which has ballooned alongside that of OpenAI. On the first full day of US President Donald Trump’s second term, Altman appeared at the White House alongside Trump, Oracle co-founder Larry Ellison and SoftBank’s billionaire tech investor, Masayoshi Son, to announce Project Stargate, an audacious $500 billion commitment to AI infrastructure in the US. It was an extravagant move, befitting a maximalist president and a risk-loving investor like Son. But it was Altman who wanted to go even bigger. “We discussed, and he said ‘More is better’,” Son tells Forbes. “More is better.”

Altman says Trump has been easy to work with when it comes to AI, though the administration’s nationalist policies don’t quite align with his own or OpenAI’s. “His job is to make sure America wins. And I view our mission as for all of humanity,” Altman says. “There’s some opposition there.”

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That said, as OpenAI makes a sprawling land grab for the future, there are also some synergies in their expansionist tendencies. Beyond ChatGPT, Sora and whatever Ive is really working on, the company is building a custom AI chip, a social media application to compete with X, and is even considering humanoid factory robots. In January, OpenAI announced a suite of software tools for health care organisations and a freemium ad-supported business model for ChatGPT. OpenAI chief research officer Mark Chen says that in the year ahead it hopes to develop an AI researcher “intern” that can help his team accelerate its ideas.

“We are heading toward a system that will be capable of doing innovation on its own,” Altman says. “I don’t think most of the world has internalised what that’s going to mean.”

Critics look at all this and say Altman is just trying to make OpenAI too big to fail, an argument allies dismiss. “I don’t think there’s some secret plan,” says OpenAI chairman Bret Taylor. “People are just excited about the impact of AI on humanity.”

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Graham thinks it’s just Altman’s nature. “If he sees an opportunity not being exploited, it’s very hard for him not to do it,” he says, noting his former mentee has a particular weakness for things that are undervalued. “I bet he finds it hard to resist buying commercial real estate in San Francisco.”

Altman has stakes in more than 400 companies, which might suggest a certain lack of focus. Multiple OpenAI employees tell Forbes they fear the company is trying to do too much too quickly. They worry about its ability to stay ahead in the model race, particularly after GPT-5, which was widely viewed as disappointing. And they were shaken when Apple chose Google’s AI models to power the next generation of its intelligent virtual assistant Siri, a deal that was Open­AI’s to lose since it had already been powering the iPhone maker’s Apple Intelligence offering. “Yeah, that was not great,” says one engineer. “A lot of us thought that was a done deal.”

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Altman, for his part, says he is “110 percent” focussed on OpenAI and its core mission of AGI, which is conveniently hard to define and could be anywhere from three to 30 to forever years away. At one point, he simply declares victory: “We basically have built AGI, or very close to it.”

Told of this assertion, Microsoft CEO Satya Na­della serves up a reality check. “I don’t think we are anywhere close to [AGI],” he says with a chuckle. “We have a good process in place. It’s not about Sam or me declaring it.” Even as one of OpenAI’s most important partners, Nadella acknowledges natural “friction” as the companies compete in AI. “There will be grey zones,” he says. “So that term ‘frenemies’, I think, is a fine way to characterise [the relationship].”

A few days later, Altman dials things back. “I meant that as a spiritual statement, not a literal one,” he says. Achieving AGI, he concedes, will require “a lot of medium-sized breakthroughs. I don’t think we need a big one”.

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Altman is aware that his motivations can be perplexing to some. It’s “hard to know what’s going on inside his head”, says Graham, his longtime mentor, someone you’d think would have at least a general idea. The OpenAI CEO’s insistence on scaling immediately and aggressively often draws criticism. Take his headline-grabbing commitment to spend $1.4 trillion, mostly on AI chips and data centres, over the next eight years. In his mind, it’s “obvious” it will take that amount of money and computing power to keep up with the exponential growth of AI use. “Then the rest of the world is like, ‘financial reality’. And I don’t think I’m the strongest at keeping those duelling perspectives in mind,” he says.

Altman has a pretty simple succession plan for Open­AI: Hand off the company to an AI model. If the goal is for artificial intelligence to become so advanced that it can run companies, he asks, then why not his own? “I would never stand in the way of that,” he says. “I should be the most willing to do that.”

And then what? He says he has no professional ambitions beyond OpenAI, with one caveat: In a post-AGI world, he might find passion in a new type of work not yet created. “The things I really wanted to accomplish, I’ve mostly accomplished,” he says. “I feel like I’m playing for bonus points at this point.”

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First Published: Mar 26, 2026, 15:48

(This story appears in the Mar 20, 2026 issue of Forbes India. To visit our Archives, Click here.)

Next Article

AI is cheaper than human labour: Sam Altman

The OpenAI chief on why AI will become cheaper than human labour, how jobs will evolve, India’s intense AI momentum, and the resource and learning trade offs societies must prepare for.

Last Updated: Mar 26, 2026, 11:04 IST5 min
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OpenAI CEO Sam Altman. Photo by Anna Moneymaker/Getty Images via AFP
OpenAI CEO Sam Altman. Photo by Anna Moneymaker/Getty Images via AFP
In a Nutshell
RAPID READ
  • AI is already cheaper than human labour, says Sam Altman
  • India is OpenAI's fastest growing market for Codex
  • AI will reshape jobs, requiring adaptability and new skills

At a closed door conversation with select editors, OpenAI CEO Sam Altman spoke candidly about the accelerating economics of AI, the shifting nature of work, and the strategic choices countries will face as the technology becomes deeply embedded in daily life. From India’s rapid adoption of AI tools to questions of energy use, learning, and the future of personal agents, Altman offered a wide angle view of how the next phase of AI may unfold. Edited excerpts:

On AI being cheaper than human labour

It will absolutely be cheaper. The energy costs of inference today—per line of code—are already far, far lower than the energy costs of a person doing equivalent work. These energy cost analogies often get weird.

People usually compare the energy cost of a human at inference time—the moment they solve something—with the total training energy of an AI model. But a person also requires a huge amount of energy over their lifetime to “train”—to grow, to run their body and brain for decades, not to mention the evolutionary process that operated at vast scale to produce human intelligence in the first place.

So, these models are already surprisingly efficient per token at inference time, relative to the energy required for a human to generate a token of thought. I expect that efficiency to continue improving significantly. My view is that, per unit of intellectual capability, energy cost will not be the dominant factor—the models will be extremely efficient.

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But because we will use such large volumes of AI, the global energy footprint will still matter.

On reskilling and jobs

In terms of jobs, I absolutely expect AI to have a big impact on the jobs people do today. For many jobs it will be a partial impact; some jobs will change entirely; and totally new jobs will be created. It wasn’t very long ago that the job that is now the most popular among American students entering university—being a YouTuber—simply didn’t exist. It’s a reminder that when new technologies emerge, new kinds of jobs emerge too.

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Which is also why the reskilling question is so hard. I wouldn’t have known to tell anyone to train to be a YouTuber—and maybe I still wouldn’t—but right now we’re in a moment where it’s difficult to say what the best jobs will be 10 years from now. There are skills that will certainly matter: Resilience, adaptability and fluency with AI tools. When I was at university, everyone was told they needed to learn to code. That was good advice at the time; it’s probably not the best advice now. But I do think everyone needs to learn to become skilled at using AI tools—and that will be important.

On resource trade-offs

More of the resources required today go into inference rather than training, and that will continue in the future. In fact, I think that ratio may increase over time. So the bigger question won’t be whether a country should invest its water power or other resources into training frontier models—although that is a question—but rather how a country wants to balance the need or desire for local inference with the resource trade-offs, or whether they would prefer, for lack of a better word, to outsource that to another country.

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On India as a large revenue market for OpenAI

What is happening in India with AI is truly remarkable. The country has a strong conviction to invest across the entire stack—from the infrastructure layer to the model layer and to the application layer on top. The rapid adoption of AI tools by people here is really striking.

It’s our fastest growing market for Codex; someone just told me it may become the largest Codex market soon. I don’t yet know what this will mean for the country in the long term, but I don’t know of any other country adopting AI with more vigour.

My sense is that, at the very least, we’ll see an incredible new generation of startups doing great work here. I think India has to be a revenue market. One thing that’s different about AI compared to previous internet services is that the cost of delivering these services is simply higher. So, to meet the volume of AI usage India will demand, we’ll have to find ways for it to be an attractive market as well.

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On concerns around cognitive offloading

If we don’t adapt and if we don’t change how we teach children, that would be a real problem. When I was in junior high school, Google came out and my teachers panicked. They said, “There’s no point teaching history or anything else if you can just look up any fact instantly. Your brains are going to rot.”

They wanted us to promise not to use it because, in their view, it removed the reason to learn. All of us said, “This is ridiculous. As adults we’ll be able to use Google at work—so let’s use our brains for something else.” It took a little time, but the education system eventually adapted. It is important to learn how to think.

There are things I learnt—like how to write an essay—that I’m still glad I learnt the old-fashioned way, because they taught me something about how to think, and that remains useful. I suspect that if we make no changes to how we teach and assess students, then yes, they might end up doing too much cognitive offloading to these tools.

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But the right answer seems to be to assume we are moving to this next level of technological capability—that people will have these tools—and then develop new ways to teach, challenge and evaluate them… assume the tools exist, but still require people to think, be creative and stretch their minds.

On AI investment returns

I think that depends on the group of people running each company. They will look at projected forward growth rates and decide how profitably, or how unprofitably, to operate in the short term.

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On the battle over personal agent models

The models are not good yet. I think what will hold back personal agents is making them safe and secure enough that you can trust them with your personal data, without the risk of something like a prompt injection stealing all your information. So, I think as soon as we, or someone else—really, the field as a whole—can develop a solid framework that users can trust from a safety and privacy standpoint, I would expect rapid adoption of personal agents.

First Published: Mar 26, 2026, 11:39

(This story appears in the Mar 20, 2026 issue of Forbes India. To visit our Archives, Click here.)

Naini Thaker is an Assistant Editor at Forbes India, where she has been reporting and writing for over seven years. Her editorial focus spans technology, startups, pharmaceuticals, and manufacturing.
Next Article

We'll drive AI costs down far more than anyone thinks possible: Sam Altman

The OpenAI CEO on how AI will reshape today’s jobs, India’s rapid adoption of the technology, and why empowering people—not concentrating power—is key to the future of AI.

Last Updated: Mar 25, 2026, 14:20 IST4 min
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OpenAI CEO Sam Altman. Photo by Cody Pickens for Forbes
OpenAI CEO Sam Altman. Photo by Cody Pickens for Forbes
In a Nutshell
RAPID READ
  • Sam Altman says AI costs will drop more than expected
  • OpenAI aims to democratise AI, not concentrate power
  • India's energy in AI development is remarkable

At a closed door Q&A with select editors—attended by Forbes India—OpenAI CEO Sam Altman offered a wide ranging view of where advanced AI is headed next. From models that can now discover new knowledge to the rising costs of frontier systems, the future of software, India’s place in the global AI stack, and the need to democratise powerful tools, Altman spoke candidly about both the opportunities and risks ahead. Edited excerpts:

On models’ intelligence

The most important development, in my view, is the models’ ability to discover new knowledge. We can debate how the models perform on different evaluations, where they are strong, and where they are heading. But something that has been happening over the last few months is that the models are now discovering new knowledge.

There was a recent physics result that genuinely seemed to astonish many physicists. Even those who had been sceptical said, “All right, maybe AGI is pretty close.” Recently, we took part in an initiative called ‘First Proof’, which involved 10 research level mathematics problems that were publicly known to have no existing solutions. I believe our model was able to solve seven of them.

I’ve heard this has converted some of the biggest sceptics. I think this may be the most important evaluation remaining for assessing model intelligence and capability.

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On the software industry’s future

I think a lot of it will change. But people overreact to both the positive and the negative. I think people have forgotten that much of what makes a good company—it goes well beyond software. So if you have a database, available user data, whatever it may be—even if somebody else can write the software just as easily—it doesn’t necessarily mean it will become an effective competitor.

It is true that software is now far easier to create than ever before. I’m sure that will be quite bad for some software companies. But many software companies have a value proposition that is quite different. I think this is going to be the greatest era for new companies… we will see an explosion in new value creation.

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On India building and competing with global frontier models

The question was not whether I thought India or anyone else would compete with frontier models, but whether you could do it for $10 million. I didn’t think then—and I don’t think now— that you can make a frontier model for $10 million. In fact, if anything, I’d say that has become harder. The compute costs, the total complexity, the overall costs have all gone up.

But, of course, there are incredible small language models being built, and I suspect we’ll continue to see models for narrow applications being created for smaller and smaller amounts of money—and more and more companies doing that very well. The building energy in India is quite remarkable, and I’ve never seen such a relentless amount of energy attacking the entire stack anywhere else.

On concentration of AI

I do share the concern about the concentration of AI. Our stance is that the only path forward is to heavily democratise AI and to put these tools in the hands of people—even if that comes with some downsides, even if it means society has to wrestle with some big challenges.

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But everything I’ve studied in history suggests that concentrating all AI power in the hands of one company or one country—even in the name of safety—would be a disastrously bad thing to do.

We introduced a strategy, at least within our field, called iterative deployment. The idea is that we release AI early into the world, allowing people to become familiar with it and to use it even when it’s imperfect, even when it has flaws. That doesn’t mean we aren’t responsible in how we do it. It doesn’t mean we don’t begin conservatively. But it does mean we empower people to do things with the technology that we ourselves might not like.

It means we try to encourage a robust ecosystem to be built around the world. It means we accept the trade-off of empowering people and accepting that society will have to wrestle with something new, rather than trying to hold on to all the power ourselves and claiming we could guarantee this or that outcome.

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On AI regulations

I think different countries are going to try different approaches, and then we’ll learn from what works and what doesn’t. I suspect we’ll move more towards global standards. But even then, it will never be exactly the same everywhere.

Different countries will say, you know, “total ban on social media for young people”, “partial ban”, “no ban at all”, and we’ll observe how it goes over time. For AI, similar things will happen. Some people will say, “If content is used with an AI tool for assistance at all, it counts as AI content.” Other countries will say there’s no difference. Some will fall somewhere in the middle.

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On capital needed for AI companies

I’ve been a bit confused about how much capital we’ll need, because revenue is growing so quickly that we may end up needing less equity capital than we originally expected. We’ve also been able to make more progress than I thought in funding partners who will help finance compute for us through non-traditional arrangements. I would say our thinking on that is continuing to evolve as the market develops. And three to five years out is extremely difficult to forecast.

On making AI more affordable

I just saw a statistic the other day: The cost of getting a difficult, high quality answer out of our models has fallen more than a thousand-fold since two Decembers ago—so roughly 14 months. It is incredible. I don’t know if we can repeat that level of reduction in the next 14 months—I suspect we can’t. But I’m optimistic that we’re going to drive prices down far more than anyone thinks is possible, reasonable or likely. I think that will help the Global South too.

First Published: Mar 25, 2026, 14:26

(This story appears in the Mar 20, 2026 issue of Forbes India. To visit our Archives, Click here.)

Naini Thaker is an Assistant Editor at Forbes India, where she has been reporting and writing for over seven years. Her editorial focus spans technology, startups, pharmaceuticals, and manufacturing.
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