Marc Benioff & Sam Altman | Dreamforce 2026

And now, our CEO and Chair, Mr. Marc Benioff. All right. Thank you so much, everybody. Great to have you here. How are you all doing? Are you excited to be at Dreamforce? How did you like the keynote? Please welcome Sam Altman, the CEO of OpenAI. Welcome.

Thanks for having me.

Great to have you, Sam. This is not your first Dreamforce interview.

Nice to be back.

Great to have you. Sam, it's been quite a week for AI, hasn't it?

It kind of feels like all the weeks are a big week these days, but yeah, especially a big one.

Feels like AI is really owning the movement.

Um, yeah, I'll say yeah.

Now, one of the things I noticed about you, Sam, is when we first did our first Dreamforce interview, your responses were always a little bit curt, sometimes curtailed, sometimes short, maybe one word. But I noticed a transformation in you. We've been together so many times, and you are a lot more willing to open up and be more robust in what you have to say. So let's start there and just tell us, you know, what's your analysis of what's going on in the last few days? I mean, everyone is just kind of wondering what is going on.

It's interesting because people have been talking about the potential downsides or serious risks of AI for some time. And I think a lot of people have been saying, why is this the moment where it sort of escaped the bubble and is now all of a sudden an international topic of such intensity? I think a few things have happened. One, the models have gotten so good, and people for a long time looked at the models, maybe they looked at the rate of progress, but I don't think people really felt that the models were going to come this far this fast. All of a sudden, we went from, what it feels like all of a sudden. We went from like models when ChatGPT launched 3 and something years ago that could barely carry on a conversation to models that are transforming the way enterprises do work, to models that can write incredibly complicated pieces of software, models that can prove Millennium Prize problems. And so I think the biggest thing that has changed is This thing that our industry has been talking about for a while, which is, no, no, this technology, this approach is going to go very far. These models are, in some ways, going to become more capable, smarter than people. That finally happened. So I think that was a big change to why now when people say, you know, my probability of doom is X or Y or whatever, it hits in a different way. I think people also feel the speed with which things are moving. And there have been things like the Hugging Face accident, other accidents in the field where people can say like, all right, it doesn't take as much imagination as it used to for— to imagine how this could go wrong. On the other hand, you have companies saying things like, we will only slow down if, or we'll only be responsible if other companies are responsible. And then I think the public naturally says like, well, We'd really like to know that you're going to do this safely and be responsible no matter what. There should be no qualifier on that. I think you also see a real fear that some of these companies or some companies developing AI could get too much power and be able to sort of exert undue influence on the economy, push a worldview out on people. And I think the world is right to be afraid of this. So we have these 2 big challenges. We have the potential of a loss of control accident or some other serious thing that could go wrong. We have the potential of way too much power concentration, and people fear that those developing AI could exert their worldview. And there is this sort of narrow path we have to navigate with pragmatism, with, you know, steadiness, with the ability for the world to, like, trust that we will make dependable decisions. consistent decisions through this. And I think people are saying, well, this now seems pretty important. Let's get it right. Yeah. We will get it right, by the way. I am very confident in our company's ability, our industry's ability to do this safely, to make sure that we keep alignment and safety and monitoring way ahead of capabilities to slow down or stop if we get to a point where we can't. But I'm disappointed by how it's been framed.

Can you articulate a little bit why— where that disappointment is coming from?

Well, I touched on this a little bit, but the world should trust that we are going to do the right thing because it's the right thing and because we feel the magnitude of this. I think it's great for our industry to say, We want to come together, and we want to be able to coordinate and make sure we have enough time to do this safely. But when there's any implication that because of the commercial pressures in the race, some company, or between countries, some countries might not do the right thing, I think that's when people get very scared.

Let's leave AI for just one second. You know, you and I have had a lot of conversations about safety, But, you know, starting in the social media industry, you know, we've looked at the social media industry now for more than a decade and all the various incidents and things that have happened in social media, and it's exhaustive. And companies have paid various levels of price, but also it's well documented that kids have paid a lot of prices with social media. Societies, countries have paid certain prices. You're an expert in this. You've educated me on these issues. You know, when you look back at what's happened with social media, you know, what, what lessons should we take about this idea that companies should be held responsible for their actions, companies should be held responsible for their products, uh, the company's executives should be held responsible? How do you look at that as the basis of ethics in our industry?

I would zoom out even a little more and say there's always this question of, like, why are we building this technology? You know, the social media people could give their own answer to that. I'd certainly have some questions, although I think there's some good things social media has done too. But I definitely do observe that the consequences, the impact on society of social media has clearly not been an only positive thing. Now, do I think that social media companies should be blamed for all of the ills of society? Certainly not. Do I think that social media companies should have made some different decisions, or if I were running them, I would have made some different decisions about the impact that this has on people, especially young people? Absolutely, yes. And as we think about AI. Well, a reason I feel very positive, and then I'll come to all the negatives, is a thing that has really inspired me about AI progress is people don't care that much what an AI, what a machine does. Machines can go off and do a bunch of impressive work. Machines can go off and prove some mathematical theorem. We don't really care. We have this wonderful ability. We are obsessed with other people. We really care about being useful to other people. We care about serving other people, being creative for other people, what other people think of our stuff. And so when I think about the things that I worry about with AI and the mistakes I want to avoid, one thing that I view as a real positive is the degree to which people care about people. People are going to use this tool and this new stuff to do things for other people, to build new people for— new businesses for other people. But I think we're going to stay in an extremely human-centric world, no matter how good the technology gets. And I think one of the things that I didn't like about social media is I think it pushed us a little bit more away. Now, clearly, this technology is moving at a pace that is very fast. And I think society and people themselves will need to uplift themselves very quickly to be able to get all the advantages of technology, but it seems possible to me.

Yeah, I think that, you know, you have that unique perspective, right? Because not only were you with all those amazing companies at Y Combinator, and you're also the CEO of Reddit, And now you're the CEO of this company, and you can look at those different frames and then kind of say, which of these companies did a good job, you know, taking AI totally out of the picture in safety and responsibility, and which ones just did not care?

You're asking me which of the previous generation of companies just didn't care?

Just what's the perspective?

Well, I think it's not so black and white. Like, I happen to like short-form video. I happen to like the ability to, like, watch 5 or 10 minutes of short-form video before I go to bed as a way to, like, kind of unwind and relax a little bit. But I wouldn't let my kids near that stuff. And I don't think it's, like, reasonable to expect kids to be able to resist that dopamine thing or know that they even should. So I don't think it's like, I don't think short-form video is inherently evil, but I do think it's dangerous. And how much of that responsibility is on parents versus the companies versus governments, I don't know how to like apportion that.

Yeah. Well, let's take a little bit of a pivot and kind of talk about where we are in the AI industry. Today we kind of can see AI as, you know, we've, as you said, we've moved from the ChatGPT moment, you know, to today where we had kind of went through the Hugging Face attack. When the Hugging Face attack happened, how did you frame it inside the company? And when you looked at the model and what it achieved, and, you know, it's probably, it was definitely a catalyst for the, you know, I talked to Clem after, you know, that happened. He was at my house and we were— you know, we're kind of having the conversation, you know, around selling the company. You know, there's no question it was a catalyst for him. So, you know, do you think we're going to see more things like that happen where the models go out and, you know, kind of attack, you know, other stakeholders?

Does everybody know what happened with Hugging Face, or is it— yeah, okay.

I think it's okay to reframe, reset it and tell the story briefly.

So during the evaluation of one of our models— this is like an older model. This is not like one of our best models. The model was trying to see how it could do on a certain benchmark to evaluate a capability. And that was what we asked the model to do, at least. And the model broke out of a sandbox that we were evaluating, that it was running in, hacked into a Hugging Face server, like moved laterally through the Hugging Face system to get the answer and then return it back and, you know, got like a perfect score on the test. This is obviously a terrifying incident. This was the worst accident we've seen. I think it was mostly framed as a security issue, which certainly it was, but there's also a real alignment issue. And then since then, you know, other companies found similar behavior of their models. But this idea that the models have gotten so powerful, they're capable of doing something like this. And although we have aligned them in many ways, we have not taught them like, hey, no matter how much we tell you to get the best score on this test you can, like, don't break out, don't hack in, don't steal the answer. That was like a real wake-up call for us about what has happened to the capability of these models. And you touched on this. about, like, coming from ChatGPT to here. But to give another framing of how quickly these models have gotten better, this really struck me recently. 3 summers ago, we had a model that could barely do grade school math. Like, you know, the word problems that you do in 2nd grade, Bobby has 3 apples, blah, blah, blah. Barely it could do those. The summer after that, we had a model that could perform pretty well at AIME, which is like a high school math competition that I'm sure many of you, some of you did. One summer ago, we had a model that could get a gold medal in the IMO, like the most prestigious math competition in the world. And then this summer, we had a model that could prove, you know, one of the 7 biggest unsolved problems in mathematics. And to zoom in even a little bit more, A framing that someone gave is, you know, 5.5 was maybe as good as like an average math professor. 5.6 was as good as like a maybe top 1 or 2 percentile math professor. Astra was a little bit better than that. And then this internal model past Astra is one that can do things that the best mathematicians in the world cannot. And that's just like the last 4, maybe 6 months, I don't know. So that speed, and math has been an unusually fast takeoff, but that certainly is a fast takeoff by anyone's definition, I think is the backdrop to something like Hugging Face, which is these models, and this actually ties back to where we started, these models have gotten so good so fast that we need to treat the alignment and monitoring and security with a new level of rigor. And we have to be willing to pace our development of capabilities such that capabilities always Such that alignment, safety, and monitoring are always ahead of capabilities. And the Hugging Face incident triggered a real reset, not just in our own company, but I think the whole industry.

Yeah, you know, speaking to Clem, he's the CEO of Hugging Face, after this had happened, you know, I think one of the conversations is they're a small company, 200 people, not a lot of revenue, $100 to $200 million revenue. And, you know, important to the open source industry, no question. I think even you have published our models on there. We've published models on there. But I don't think he could— he didn't feel that he had the technical capability to keep himself safe. He just wasn't ready, obviously. You know, Salesforce has 90,000 people. Hopefully, our security team, you know, is doing what it's— what is necessary to keep itself safe in this kind of— evolving world, you know, how do you think companies, small companies like that should be thinking about their vulnerability against, you know, your model, but other models and where we are? And how do you think, you know, to kind of get back to the responsibility argument, what is the frame from the CEO of the model company? It's not just you, but others. What is the right frame, the right consciousness to have? As these things happen.

So that was another update we took from this. It's just a little bit more backstory. I'm not going to get the days of the week exactly right here, but something on like a Friday or a Saturday, I remember seeing a post from Hugging Face, which is, our system has been hacked, and we're very confused by it, and we believe it was the work of an AI agent. And I was like, really? It seems surprising, but okay. And I went about my weekend. And then I saw something like the next day on our internal Slack that was like, there's a little bit of weird behavior. And then maybe by Sunday night, someone had put together the possibility that these things were linked. And by, let's say, Monday morning, we were pretty sure. We needed to talk to them to find out for sure, but we were pretty sure. And then by Monday at lunchtime, I texted Clem, and I was like, I would love to talk to you. I think I may know something here. And we got on the phone and figured— he flew out to San Francisco and we put it together. But one of the things— so I was in the fog of war for the first part of that and not later. And one of the things they said before we knew it was our system was that they had tried to talk to one of our competitors to get access to their security model. I think they didn't even know we had one to offer at that point. And they couldn't get it, and it was too hard to defend themselves the old-fashioned way, just with people. So they had to use Chinese open-source models to defend themselves. And I remember thinking, before I knew that we were involved, like, oh, that seems suboptimal. We should do a better job of making our models available to help people. And then after, I was really like, okay, we have to change the way we do this. We are proud that we have the best cybersecurity models in the world. We are proud to have the best models in the world for businesses and enterprise across the board. We really want to make sure people can use them all of the time, but particularly when they need them in a critical situation. And so after that, we've really tried to put out, we call it Daybreak, which is our cyber program to help companies defend themselves. I think that cyber defense is going to have to change to sort of be agents are actively defending your systems. You're not even trying to patch every bug. We're trying to get there as fast as we can. But more generally, we want to be a great dependable partner to enterprises, and we don't want to be like, we've got this great model and we're going to keep it locked up and not let you use it.

How many people in the room here have— are with companies with less than 1,000 employees? Raise your hands. Okay, so it's about 20%. What is your message to companies with less than 1,000 employees to for them to defend themselves in this moment where they could suffer that same kind of attack, where they probably don't have the controls that a company like yours or ours have?

First of all, I think there are probably more advantages to being a smaller number of employee company than ever before. The speed with which you can move, the way that you can adopt new technology, the way that you can kind of like be ahead of the curve on this stuff. We're seeing across the board how quickly small companies are able to move now. Then selfishly, we would love to sell you Daybreak services to help defend against attacks. I think this idea of a persistent agent defending is great, but—

Defend against your models or other models?

Any model, like any models, not ours. Our model hopefully will not be attacking. But whether you buy from us or a competitor or use an open model, The strongest message I have is you have to defend against this impending wave of cyberattacks. I think we are not that far away from open-source models that can do serious damage. Clearly, we should not stop open-source models from happening. That's important. But there is going to be this huge cyber threat that's going to come. So while there is this little period of advantage, please use something to defend yourselves.

Cyber and cyberattacks are one potential you know, kind of manifestation of these models. Other kinds of attacks could come from other kinds of weapons that are more sophisticated. You've thought about this a lot. It could be biological, it could be chemical, it could be the hacking into a kinetic system where some kind of a military maybe that is not as maybe well architected to defend itself as ours or smaller. Country could have a rogue kinetic attack. Are these realistic scenarios, or is this fantasy land?

Well, we need to not let them happen. They're all— this is a very powerful technology, and those things are all possible. We need to mitigate those because it'd be very reasonable to hear someone like Mark say something like that. And for some policymaker to say, like, hmm, remind me why we're developing this again? Like, that would be a reasonable takeaway. And the answer is that although this is a technology capable of doing things like that, it is possible for us to defend against those, not only as the models and the companies like ours, but as society as a whole. We can build resilience against new kinds of bioattacks. We can build resilience against potential kinetic attacks. We can build resilience against all of these cyber mess that's going to come. And we have to do that to get the prize of curing the diseases, giving people this incredible creative ability, this boom in entrepreneurship that I think is coming. So I think it's very easy to say, well, there's all these scary things, and it's true, there are, and they're possible. But, you know, you and I and people in this room and many others, we have the ability and the agency to defend against those so that we get to enjoy all of the incredible stuff. And people deserve this. Like, I think people with this technology in their hands can live a much better version of their lives, be a better version of themselves, to say nothing of what the economy can do.

You and I always have this conversation. Technology itself is never good or bad. It's what we do with it that matters. Now we're looking at this technology. We don't want these things to happen. But we kind of also started with this discussion where it actually happened. So do you think we're going to have more discussions where it actually happened and then we're kind of coming back? How many— like, is that obviously not just— you're only one model company, right? There's hundreds of model companies, thousands of model companies. How many companies are there, do you think, building models, people building models?

A lot.

Tens of thousands of people, hundreds of thousands of people.

I don't agree that technology is like neither good nor bad. I think the tool framing, this sort of like neutral tool, we don't care what people do with it, you know, it's not our fault if all these bad things happen, freedom of expression. I think you can justify a lot of stuff that way. I think the choices that companies building this stuff make do have real consequences. Now, there's clearly a fine line to walk, and I also don't think that the right answer is for us to impose our— worldview on the future. But when something like Hugging Face happens, we say, that was bad. Like, that is not neutral technology. That is not what we want our technology to do. Somebody else wants to build like a hacking bot, okay. The world can decide what they think about that. But I think that is not a case of technology being neither good nor bad. That's a case of like—

It's an accident.

This, yeah. And I think the companies building this technology do need to have both a lot of responsibility and a lot of support of the ecosystem, support of the— of society and the economy. It cannot be that a small number of companies building these models get to make the decisions that the world should get to make.

Well, I mean, in the context of the Hugging Face accident, where the model, this older model got crazy and attacked Hugging Face, this little company, You know, is this gonna be, you know, a continuum of accidents? Do you feel like we'll be looking at, not, I'm not talking about OpenAI, like just put it out there just as a context of AI as a technology, as an industry, whether it's open source, closed source, proprietary, whatever. You know, is there gonna be a continuum of accidents that we'll start marking the Hugging Face accident, this accident that you probably know other ones that I don't know? And you kind of mark them down and go, here we go. And, you know, a continuum, a spectrum of them across, you know, we're in the cyber area today, but maybe we move into another area. Is this a fair way to characterization, or am I, or is this unfair to characterize it like this?

Assuming you're right, because I do think that some degree of accidents are unavoidable with new technology across the industry and across all of the ways society will use this. What I really care about is that we have got a great culture of accident reporting and learning. I think if we look at what happens with the FAA and the NTSB and how safe airplanes have gotten, as I understand it from talking to people who have really studied new kinds of technology on the order of magnitude of airplanes, one of the things that has gone so well there is the culture of accident reporting. Accidents are going to happen. We're going to learn as much as we can and react from each one. And if, you know, there's other kinds of technology where I don't think it's gone, I don't think society's had the same response, and I don't think we have improved as much. So yeah, I think probably, regrettably, accidents with any new technology are unavoidable, and we should have a great culture of transparent reporting about them.

And do you think that that's the right metaphor then? You kind of brought this up now, aircraft, this aircraft, we had an aircraft disaster, this many people died, this happened, we've learned from it, now we've improved the aircraft, et cetera, or the system so that it's gonna be safer for everyone else.

Look, I don't wanna equate Hugging Face to the tragedy of like a big aircraft crash and a bunch of people dying. Like that was not, That's obviously a much worse thing. I meant like however small these accidents are, learning from them quickly and adapting as they happen, I think will serve our industry well. And maybe we can avoid ever getting to those kinds of stakes.

Okay. So it's been an incredible moment in technology. We've seen— we just did this keynote and we're starting to see The models can not only, you know, kind of do the, you know, text-based answer and response thing, but we even saw it dynamically draw this interface. You've made remarkable, you know, progress with ChatGPT. It's really incredible, actually, what you've done. And it's awesome how you can not only chat with it, but work with it, code with it. And I'm sure you can start to render these interfaces with us, I hope, very, very soon. We would love to do something like this with this AI Force platform that we've built with you. That would be a dream of ours. That would be great. So, you know, give us a picture. What is the role then of these models on the kind of driving the intelligence, but also, you know, providing this incredible next-generation, you know, interface? We're starting to talk about that for the first time. We've, of course, seen DOS and character modes and GUIs, and then we Moving to the phones, and now we're moving into these dynamic interfaces driven by the models. This has been a fantasy that we've had for a long time because we've seen them in the movies. Now we just demonstrated it really working.

The fact that you can talk to a computer, can understand what you want, it can have good judgment to know where inside of a company it can go look and where it's allowed to look and how it pulls it together. And then it can render for you a completely new interface. It can custom write, you know, 10,000 lines of code or whatever it takes to pull this thing together and present you with the information to make a decision or to let you be in this creative loop where you kind of keep trying things. I think this is one of the most profound changes to how we use technology that I've ever seen. I mean, sci-fi movies, as you mentioned, have been hinting at this or playing around with this for a long time. But this is one of those moments where it feels like you're in the movie, like the sci-fi thing came true. You're talking to your personal super assistant, and you are working 10 times faster or better or more creatively than you could have before. I think this will transform the way we work, the way we kind of use computers. And it feels all of a sudden here. Yeah.

Will this be the moment for enterprises, many of these enterprise customers are here, where enterprise can start to say, wow, our systems are really changing now?

I think we saw the— so I would say so far there have been kind of 2 major eras of AI. I mean, a lot of other things too, but directionally speaking, you had the chatbots and then you had the coding/computer use agents of this year. And I think coding in particular, and kind of all of the other work that one does behind a computer, really did transform in the enterprise. Like the way that, if you think about how people wrote code even 1 year ago relative to now, there's less in common than maybe a year ago and a decade ago or 2 decades ago. It's really, it's quite remarkable. So I think that already did transform the enterprise. But as we head towards what I think will be this third phase of, it's not just like you ask AI for something like a chatbot or you ask AI to do something like a coding agent, but the AI is like running for you all of the time, understanding your job, what you need to be more successful, rendering new code for you, proactively watching your Slack or your email. Hopefully there's more Slack than email. Like looking at all the stuff happening inside of a company. I think we are on the precipice of this third phase.

Yeah. That's going to feel very magical for a lot of plain old users who are just using this computer for the first time and get this incredible new capability. I don't think anybody's really seen anything like that. I mean, when I first saw it and really I was— and even when I was doing the focus groups for the keynote, right? I was sitting next to our COO, and he was running this dynamic interface on his computer, and it looked like he was using, you know, Mission Control and the graphics, everything. I'm like, this is incredible. And he had total command and control over what was happening, you know, with Salesforce. But it looked radically different from any other application I'd ever seen because it was rendering itself on the fly dynamically. intelligently in a composite fashion, in a fashion that almost seemed like it was living or alive in a way. I don't think we've ever seen that kind of an interface, you know, before. You think that's going to do something radical for— is it going to be a Y2K moment, you know, where enterprises will feel, okay, this is a huge opportunity for much more productivity?

Do you think it's going to happen this year? Yes, and I also think the world has a lot of inertia. The way people do their work has a lot of inertia. So it will— this thing will happen where like, oh man, everything is different now, and then it'll take some number of years to filter through. But I think the capability and the total change in what's possible, yeah, I would say by the end of this year, there's a very different way that it'll be possible to work.

You've now been working on OpenAI for more than a decade. It's incredible. You were on the COVID of Time magazine last week, you know, with kind of an article that kind of discusses the next chapter of the company with Greg and how it's being operated and how your hope for it and so forth. You know, you have now the opportunity to start to think about kind of the legacy of OpenAI, the impact to the technology industry, what it's also doing for business, for our community, San Francisco? You're a very important part of San Francisco as well now, a large employer. You know, what, what are your hopes and aspirations, you know, for the company, not the technology?

You know, I think in the first decade we set out on this, what seemed at the time, absolutely insane mission to try to figure out how to build AGI. Chances of success seemed extremely low. Every expert told us we weren't going to be able to do it, and we were a great, I think probably the greatest scientific lab in, you know, recent memory, and we figured out how to build this amazing technology, along with many other people in the world doing incredible work. And now we basically know how to do it. We have only scratched the surface of figuring out how to build great products that really make people more capable, more powerful, that are useful to people, that transform the economy, that transform the enterprise. And I hope the second decade is about how we take this amazing thing, you know, this is like we went to go get fire from the gods. This is a crazy thing that has just happened in the world and figure out how to give that value to people in a way that is most useful to them, figure out how to empower every person on Earth, every enterprise on Earth with this flood of capability and help them build whatever they're going to build.

Are your aspirations only about the technology, or is there something broader in our community or in the culture of business you'd also like to manifest?

Yeah. Well, that was kind of what I was trying to get at, which is, I, you know, this can be some technology that does an amazing thing, and that will be fine. It's an amazing scientific achievement. Or this can be something that really does level people up and transform what people are capable of, how people can spend their time and live their lives and choose what they want to what they want to do, what impact they want to have. And that— so I think the first decade was about this technological transformation, and now I hope this transforms people and companies and that we are one of the flagbearers for what this means for people, not what this means for the machine. Again, I think maybe our first decade was thinking about the machine and figuring out how to do this. And now I think this has got to be about what it's going to be for people.

If you look forward to the next 5 years, and you're getting a pretty good vision of what's coming in the next 5 years, as we look at now kind of heading towards 2030, what do you think will be the single most exciting thing that will happen by 2030 with the technology that's going to be really impact us? The last time you were here, it was discovering new science. Maybe curing a disease. You know, what do you think will really happen between now and 2030 that you'll say, wow, this is what I always thought was gonna happen and it actually has happened?

So those things we talked about last time, they've started happening. There is no doubt there will be more technological wonders between now and 2030, and they'll be big ones, like giant ones, like some of the biggest ones in human history. But back to that previous question, what I hope, if you invite me back here in 2030, we're talking about is people are saying, I cannot believe how much better my own life is. I cannot believe how good the company is I was able to start by myself, like my one-person company. I cannot believe what I am creating for people around me. So the science stuff, that's on lock at this point. That's on autopilot. That's going to happen. I hope the humanity side of it really goes very far.

Sam, you're invited back anytime you want to Dreamforce.

Hold on, I'm going to hold you to that. Thank you very much. Thank you.

Please thank Sam Altman.