Marc Benioff & Sam Altman | Dreamforce 2026

And now, our CEO and chair, Mr. Mark Vinioff. 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. 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. It feels like AI is really owning the moment. 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? And 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. And all of a sudden, we went from, what it feels like all of a sudden, we went from like models when ChatGPT launched three 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 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 will only be responsible if other companies are responsible. And I think the public naturally says like, well, we'd really like to know that you're going to like 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 two 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 a sort of narrow path we have to navigate with pragmatism, with steadiness, with the ability for the world to trust that we will make dependable decisions, consistent decisions through this. And I think people are saying, well, this now seems pretty important. I'm like, 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 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 and 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 and I have had a lot of conversations about safety, but starting in the social media industry. 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 and so 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. When you look back at what's happened with social media, what lesson should we take about this idea that companies should be held responsible for their actions? Companies should be held responsible for their products. 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 why are we building this technology? 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. 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 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're 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 for other people, to build 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 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 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? Well, I think it's not so black and white. I happen to like short-form video. I happen to like the ability to watch five or ten minutes of short-form video before I go to bed as a way to unwind and relax a little bit. But I wouldn't let my kids near that stuff. And I don't think it's reasonable to expect kids to be able to resist that dopamine thing or know that they even should. So 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 portion that. Well, let's take a little bit of a pivot and kind of talk about where we are in the AI industry. You and I, as you said, we've moved from the chat GPT moment to today where we 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? It was definitely a catalyst for the... I talked to Clem after that happened. He was at my house, and we were kind of having the conversation 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 very briefly. So during the evaluation of one of our 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. It's obviously a terrifying incident. But that's what 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 ChatGBT to here. But to give another framing of how quickly these models have gotten better, this really struck me recently. Three summers ago, we had a model that could barely do grade school math. Like, you know, the word problems that you do in second grade, Bobby has three 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. A model that could prove, you know, one of the seven 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 one or two 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 real world cannot. And that's just like the last four, maybe six 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 to be willing to pace our development of capabilities 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. Speaking to Clem, he's the CEO of Hugging Face, after this had happened, I think one of the conversations is they're a small company, 200 people, not a lot of revenue, $102 million of 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 Salesforce has 90,000 people, hopefully our security team is doing what is necessary to keep itself safe in this evolving world. How do you think companies, small companies like that, should be thinking about their vulnerability against your model, but other models, and where we are, and how do you think, to 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 That was another update we took from this, it's just a little bit more backstory, I'm not gonna 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 an internal slack, it was like, there's a little bit of weird behavior, and then maybe by Sunday night, someone had put together the possibility 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 Clement, I was like, I would love to talk to you, and he flew out to San Francisco, and we put it together, but one of the things, so I kind of like 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 from people, so they had to use Chinese open source models to defend themselves, and I remember thinking before I knew that we were involved, 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 when they need them in a critical situation, and so after that, we 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 or 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 not let you use it. How many people in the room here are with companies with less than a thousand employees? Raise your hands. Okay, so it's about 20%. What is your message to companies with less than a thousand employees 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 I's have? First of all, I think there are probably more advantages of an 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 be ahead of the curve on this stuff, we're seeing across the board how quickly small companies are able to move now. And then, selfishly, we would love to sell you Daybreak services to help defend against attacks, and I think this idea of a persistent agent defending is great, just like any model. It's 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 cyber attacks. 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 cyber attacks are one potential 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 that is not as well architected to defend itself as ours or a smaller country could have a rogue kinetic attack. Are these realistic scenarios or is this fantasy land? We need to not let them happen. This is a very powerful technology. Those things are all possible. We need to mitigate those and it would be very reasonable to hear someone like Mark say something like that and for some policymaker to say hmm, remind me why we're developing this again? That would be a reasonable takeaway. 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 bio-attacks. We can build resilience against potential kinetic attacks. We can build resilience against all of this cyber mess that's going to come. 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. I think it's very easy to say there's all these scary things and it's true, there are 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. 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 started with this discussion but we also started with this discussion where it actually happened. Do you think we're going to have more discussions where it actually happened and then we're coming back? You're only one model company. There are hundreds of model companies, thousands of model companies. How many companies are there that are building models, people building models? Thousands of people, hundreds of thousands of people. I don't agree that technology is the neutral tool. We don't care what people do with it. 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. That is not neutral technology. That is not what we want our technology to do. Somebody else wants to build 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. It's an accident. 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 society and 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. Is this going to be a continuum of accidents? Do you feel like we'll be looking at I'm not talking about open AI. Just put it out there whether it's industry, whether it's open source, closed source, proprietary, whatever. Is there going to be a continuum of accidents that will 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 a continuum, a spectrum of them across, we're in the cyber area today but maybe we move into another area. Because I do think that some degree of accidents are unavoidable with new technology across the industry and across all of the way 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, 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 there's other kinds of technology where I don't think it's gone, I don't think society has 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, etc. or the system so that it's going to be safer for everyone else. Look, I don't want to equate hogging face to the tragedy of a big aircraft crash and a bunch of people dying. That's obviously a much worse thing. I meant 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 just did this keynote and we're starting to see people not only kind of do the text-based answer and response thing but we even saw it dynamically draw this interface. You've made a remarkable progress with ChatGPT. It's really incredible actually what you've done. 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. So, give us a picture. What is the role then of these models on the kind of driving the intelligence but also providing this incredible next generation 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're moving to the you know, 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, you can understand what you want, you 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. 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 I would say so far there have been kind of two 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 slash computer use agents of this year. And I think coding in particular and kind of all 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 one year ago relative to now there's less in common than maybe a year ago and a decade ago or two 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 that 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 like 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 a lot live 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 I 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 I would say by the end of this year there's like a very different way that it'll be possible to work you've now been working on open AI for more than a decade it's incredible you were on the cover of Time Magazine last week you know with kind of an article that's kind of discusses the next chapter of the company with 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 open AI 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 large employer you know 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 um 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 um 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 um how how people can spend their time and live their lives and choose what they want to what they want to do what they what impact they want to have and that so I think the first decade was about this technological transformation um and now I hope that this transforms people and companies and that we are one of the flag bearers 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 in the next five years and you're getting a pretty good vision of what's coming in the next five 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 um 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 going to happen and it actually has happened and so those things we talked about last time they've started happening there 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 the previous question what I hope if you invite me back here in 2030 we're talking about is people are saying like 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 you know I cannot believe like what I am creating for people around me um so you know 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 very much thank you please thank Sam Altman