June 1, 2026
WHEN: Today, Monday, June 1, 2026
WHERE: CNBC’s “Power Lunch”
Following is the unofficial transcript of a CNBC exclusive interview with OpenAI CEO Sam Altman on CNBC’s “Power Lunch” (M-F, 2PM-3PM ET) today, Monday, June 1. Following are links to video on CNBC.com: https://www.cnbc.com/video/2026/06/01/openai-ceo-sam-altman-coding-models-are-the-biggest-driver-of-demand.html, https://www.cnbc.com/video/2026/06/01/sam-altman-companies-talking-about-layoffs-are-using-ai-the-least.html, https://www.cnbc.com/video/2026/06/01/sam-altman-people-are-right-to-be-anxious-about-ai.html, and https://www.cnbc.com/video/2026/06/01/sam-altman-on-data-centers-in-space-were-focused-building-on-earth-for-now.html.
All references must be sourced to CNBC.
KELLY EVANS: Welcome back. And let's head out now to Saline, Michigan, where OpenAI is building its massive Stargate data center project. That's where we find our very own David Faber with a very special guest this hour. Hi, David.
DAVID FABER: Hi, Kelly. Yes, that's right. Of course, I am joined by Sam Altman, the CEO of OpenAI. We're both looking around. You kind of never get over the size and scale of it, Sam, even if you have seen it. It doesn't, you can't read the numbers and understand what you're kind of looking at.
SAM ALTMAN: Yes, every time I come to one of these sites, I'm struck again. And you're totally right. The numbers say one gigawatt this, this many jobs or tens of billions of dollars of capital. It doesn't really get across the feel of watching something like this materialize.
FABER: Yes. I mean, that said, the numbers are pretty staggering too, $16 billion just to develop the site, build the buildings, but then, in talking to Clay Magouyrk from Oracle, at least another $30 billion going into them.
ALTMAN: Yes.
FABER: And so I guess, when you talk about something like this, $45 billion, maybe $50 billion, OpenAI being the main customer, do you feel like that 50 billion will generate the necessary return for both OpenAI and for all the people financing this deal?
ALTMAN: At this point, we're very confident. We have, so, one gigawatt is a huge amount of compute, but we understand what demand looks like and how much people want to use these models and the degree to which revenue is ramping at our company and in the industry and, more than that, the degree that value is now ramping. It's not just, oh, let me try this, but people are really saying, the future of my company, the future of my scientific research program, it is going to depend on this. Can you promise me compute long into the future?
FABER: Well, can you give me some examples? I mean, because that conversation has shifted even recently sort of. Something seemed to have happened. Maybe it was the end of last year. I have heard you discuss this as well in terms of just an uptick. Maybe it was the power of the coding models.
ALTMAN: I think that was the single biggest driver at what people, of what people realized was, the coding models have so transformed how companies are doing their work and the efficiency and the speed of which they're able to build products. The coding models got really good late last year, early this year, and then another step forward in recent months. So I think you're right that that's the single biggest driver. But we are now seeing scientists really use these models and a much broader application of knowledge work beyond coding. But, yes, I think it's fair to say that coding is the magic right now.
FABER: Was a key thing.
ALTMAN: Yes.
FABER: I want to come back to that. But, back to that, let's call it $45 billion, $50 billion, I mean, the price of compute, the price of tokens continues to come down, correct?
ALTMAN: Yes, but not as fast as the desire to use those tokens at the lower price goes up.
FABER: And so that is what gives you part of the confidence—
ALTMAN: Yes.
FABER: That, in fact, I mean, again, the numbers are staggering, when you think about just, this is just one of so many projects, and yet this will consume $45 billion in capital.
ALTMAN: We still don't think the world has appreciated how much A.I., every person and every business is going to want. Right now, you still send a request to an A.I., and it does something for you and gives you an answer back. But, very soon, an A.I. will just be running for you in the background all the time, helping you with your job, looking at all your information, aware of all your context, doing as much as it possibly can to help you out. And I can already tell, in that world, I and everybody else is going to want so much more of this A.I. infrastructure than we think.
FABER: Yes. I mean, I was listening to you on a recent podcast, and, on the same theme, you said, you know, "The models are still quite dumb." I'm quoting you.
ALTMAN: Yes.
FABER: "But not far from a model that knows you well in the world." Is that what you're talking about when you say sort of the usage pattern will go up?
ALTMAN: Absolutely.
FABER: So, what does that look like?
ALTMAN: Well, for my own job, I could imagine a model, I can't keep up with all the information inside of OpenAI. I can't read every document someone writes. I can't read every Slack thread. I don't have all of the context. And so I miss interesting connections or new ideas that could make things better. And there's no way I'm going to be able to do that. But a sufficiently smart A.I. that's running all the time, that understands my goals, that understands all the information at OpenAI, everything our customers are saying and want, that could give me really great advice and say, hey, here's the thing to do in a way that I couldn't, nor could any other person do on their own.
FABER: So, is that one of the reasons why you prioritize compute?
ALTMAN: Yes. We have seen throughout, from our founding that the more compute we can provide, the lower cost of services we can deliver, the smarter models we can make, this whole stack integrated together from, if you really think about it, in some sense, we are transforming electricity into this useful tool for people. And the better we can do that, the more we can make that smart, cheap, abundant, helpful, have all your context, the more people want to use it, and we really do build that entire stack, and that is, I think, a special thing about us. But that is what we want to deliver to the world, just, like, prosperity through abundance of A.I., a lot of it, that people can integrate into their lives and work.
FABER: On the subject of prosperity, I think you have also said there are different futures. And one is a floor of up to 10-fold of what we're, what we have right now, the sort of this abundance, but still with significant inequality and sort of different variations of that.
ALTMAN: Yes.
FABER: You still believe that's kind of what we're headed towards?
ALTMAN: I think that's just one possibility. I think that it seems clear that A.I. is going to massively increase prosperity. But getting the questions of equality, fairness, distribution right, that's going to take work from all of society together.
FABER: Yes.
ALTMAN: So, I no longer have much concern that A.I. can deliver on the magic potential or the wonderful, all these things we talk about. How society integrates this and makes sure that it really benefits everyone, I think that will be the big question in the next few years.
FABER: But you, I mean, you were most recently also quoted on another key area, which is, of course, what it's going to do to jobs. You have been fairly sobering in the past when you discuss that. You seem to have sort of said, maybe I was wrong, in a more positive way.
ALTMAN: Yes.
FABER: I'm curious as to what you have seen that's led you to that conclusion.
ALTMAN: So, first of all, I should say I'm not sure. Like, I still—
FABER: Well, none of us know the answers here, right?
ALTMAN: None of us know the answer. But a positive update for me has been watching how companies have adopted codecs and other coding tools. The companies that I know that have adopted A.I. the most are also the ones hiring the most. And the companies, as a general rule, that are talking about doing layoffs because of A.I. are the ones adopting A.I. the least. But, you know, it's a convenient way to explain it. I think I underestimated how jagged these models are going to be. They do some things incredibly well, but they don't do kind of the long-term, complex task supervision well at all. And so watching people who are really good at using these models, they can do an amazing amount of work, create way more economic value than people without models could or certainly the models could on their own. And I think that's going to go on for much longer. Then there are all the other things about people really like other people and want to interact with other people. They want to collaborate. They work with other people. When they buy a product, they want to talk to a person at the company. Most people, I think, don't want to watch an A.I.-generated creator. They want to know about the person behind it. So I think we have under - and this is really good. I'm really happy about this. But I think our industry underestimated how much we're going to be able to keep people at the center of everything in an economy that is and a world that is based on people.
FABER: But, to your point, we obviously don't know the answer.
ALTMAN: Yes.
FABER: I mean, when you introduced, I think it was 5.2, you said it outperforms professionals across 44 occupations. You can understand why there may be an A.I. backlash when people hear things like that.
ALTMAN: Totally. What I wish we had said then is that it outperforms professionals at small tasks in 44 occupations, which is I think a more accurate thing. And it is the people that are using these that are now seeing incredible productivity growth, wage growth, all of the benefits from this. But I think people are right to be anxious. And I understand it. This is like a, this not even a technological shift that happens every generation. This is one of the big ones. And—
FABER: Well, if not one of, yes, maybe the biggest.
ALTMAN: Yes. And so it would be imprudent not to have some real caution around that.
FABER: Well, on that, on the A.I. backlash, and I have been speaking on a number of the leaders in the industry, who have been saying, maybe we haven't done enough to articulate the benefits, which may be difficult to do. But there's not just opposition to data centers like this. There is a more significant, perhaps, opposition to what it's going to do to society.
ALTMAN: Yes.
FABER: How do you feel, as the leader, one of certainly the key leaders in this, in terms of your ability to combat that backlash?
ALTMAN: Yes, so it's a huge challenge. And, again, as I said, I think this is like, there's something good about this. Like, society should have antibodies against too rapid of change. And there should, like, part of the reason that we believe in this strategy of iterative deployment is, we want society to see the technology. We want society to really understand what's happening and have a chance to debate, react, sort of say, hey, this doesn't make sense or this isn't going to work for me. Like, this has got to be, I have no interest in, like, building a super smart A.I. that accomplishes some nonhuman goals. Like, this has got to be about something that is working for people, and that people are at the center of it, and human values are what we drive forward. So, people should react. People should say, hey, this is what I want, and not this.
FABER: Right.
ALTMAN: I don't think it's about not explaining the benefits, because we say, hey, A.I. is going to cure a bunch of diseases. And people say, OK, that's great, but, like, that's not really my question.
FABER: No.
ALTMAN: My question is, what is my role in the future? What is my economic future? What is my agency? Like, how do I know that my kids, my family will still be able to have a fulfilling creative expression, struggle to drive the world forward, to grow, to kind of do this thing together in a way that has worked for a long time? And when you have people in A.I. say, well, yes, sure, there's going to be no jobs or 50 percent of jobs are going to go away, 90 percent of jobs are going to go away, and A.I. is kind of going to be smarter than you at everything, and we will give you some basic income, but there's like, you're not really going to have a roll. That's horrible. I mean, that is a, and, by the way, this A.I. company, maybe we're going to destroy all the jobs, we will be the most valuable company in the world. People just look at you, and you're like—
FABER: Yes.
ALTMAN: So, I think that's a terrible message. And I don't think it's that we haven't articulated the upsides. I think people actually believe us. Like, you know what, go cure cancer. That sounds great. I think we have failed to articulate as an industry how people stay in control of determining their future at every step and have a really meaningful life in all the ways we care about.
FABER: Another part of it may be the pace of change itself. I mean, you're releasing a major model, what is it, every six weeks or something like that. It's very hard, but things seem to be changing so quickly.
ALTMAN: You know, I, maybe, maybe you're right. I don't think that's, I think, at this point, people believe us that the models are getting smarter. And there was a time when the first iPhones came out that every iPhone release was a huge deal and people lined up overnight and got very excited. And now I couldn't even tell you the number of the latest iPhone. It's great. It's amazing. It's my favorite piece of technology. But I expect it to continue to get better, and they, I know they make a new one every year. I kind of think the same thing for this technology, which is, people expect the models to keep getting better.
FABER: Right.
ALTMAN: What they really want to know is, like, what's going to happen with society?
FABER: Yes. And none of us, I mean, you don't really have the answer. You can guess.
ALTMAN: Of course I don't have the answer entirely, but what I can say is, our whole effort, our whole company is about giving this new kind of infrastructure at massive scale to people and trusting that the democratization of power, of wealth, of opportunity, of agency will continue to do this incredible story of civilization going forward.
FABER: I'm, sorry.
ALTMAN: No problem.
FABER: We're trying to figure out how much time you have left with us.
ALTMAN: No problem.
FABER: But we're in this race with China. At least, that's the way it's described. And that is one reason why we're just full speed ahead. Don't stop.
ALTMAN: Yes.
FABER: Build as many data centers as you can. Move as quickly as you can.
ALTMAN: I think in some ways, that's okay, and in some ways that's really dangerous. Like, I think it's fine to say, hey, we are gonna win this, we're gonna have, you know, most of the economic benefit. There will be some global scale safety issues, and we have had time in the past – times in the past, like with the IAEA for atomic energy and weapons, where the world comes together and says none of us should be taking global risk. Different countries, different systems, they can sort of say, you know, I'm going to treat economics this way, you're going to treat that way, I'm going to think about using AI in healthcare this way, you're going to think about using it that way. But on the really big things, making sure we don't ever lose control of AI systems, cyber security, bio security, I think we need to not treat this as a race and treat this as a, like, a good future of the world is in everyone’s interest.
FABER: That's not where we are right now, though.
ALTMAN: Well, I think we're still in the economic – I don't think we're – I think we're transitioning to a world where we have to think about that. I think we're still in a this is mostly an economic story. But as the risks – potential risks have increased in the last few months of the last year, I have been very heartwarmed by, you know, a new recognition among leadership companies and governments that, hey, there's a category here we have to treat differently. I mean, you know, I read the news about Trump's visit to China recently, and I know they talked about this. So I think people are taking this seriously.
FABER: Yeah, I mean, when we talk about a race, Sam, you are also in a race with your competitors as well. One of them is Anthropic. I'm sure you heard today they filed. Used to be confidential, apparently it's not anymore –
ALTMAN: I just heard.
FABER: – for their, you know, I'm curious as to what goes through your head. Is there a race for the – to be the first of – to come public?
ALTMAN: I don't think, no. Not for that. I think there is a race to deliver the best technology and build the best business. But, you know, going public is a financing event, and I don't think that's one that we're focused on the timing of. We'll do it when we think it makes sense.
FABER: But you will do it as well I assume.
ALTMAN: I assume that’s something – yeah.
FABER: – at some point. And when it comes to sort of that competition, I mean, again, back to sort of where we started with how much money is being spent, are you confident that all – you know, that you – that it's not a winner take all?
ALTMAN: I'm confident it will not be, yeah. I think the world will demand – this is going to be such critical infrastructure for so many things that the world will rightly demand robustness in the system of multiple providers. I think it's a very good thing.
FABER: And you think the compute, you know, the last week I was hearing about compute, for example, companies starting to wonder, well, what are we spending it on? Our bills are going through the roof, and it's not clear to us exactly what – you know, in other words, I know a lot of my spend is going well, but I don't know which part of it.
ALTMAN: So I think this is the most fair contribution – criticism right now of AI, which is, you hear companies saying, I am spending a ton of money on AI. And I know some great stuff is happening, but I know there's a ton of waste, and you know, when – how long do I have to wait for it to really show up in revenue, and how long do I have to wait to really get the costs under control? And I assume that the industry will figure that out pretty quickly, but I think that is a fair, a fair issue.
FABER: You do.
ALTMAN: Yeah.
FABER: Quickly being –
ALTMAN: I would bet that by another year or two from now, there is a much better rationalization of companies' spend relative to outcomes.
FABER: And finally, Sam, are we ever going to see things like this up in space?
ALTMAN: Ever? I hope so. In the short term, I think it's probably better to do it – you know, there's like, as you can see, this is a huge project.
FABER: Be a lot to put up there. Yeah.
ALTMAN: Putting this in orbit at current launch costs, making that lower launch cost feels difficult. Also, you know, we know how to pull it here. We know how to get people to service it here. We have an atmosphere protecting us from some radiation. I hope that humanity expands to the stars some day, and data centers along with it. But we're going to focus on building on Earth for now.
FABER: It doesn't sound like you think it's happening anytime soon.
ALTMAN: It's not a short-term priority for us.
FABER: Sam, thank you for your time. Appreciate it.
ALTMAN: Thank you.
FABER: Look forward to further conversations I hope.
ALTMAN: Enjoy.
FABER: Sam Altman, CEO of OpenAI. I'll send it back to you, Brian.
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