Watch Live: OpenAI Co-Founder Greg Brockman at WSJ Tech | WSJ

Thank you. Great to be here.

Well, something that I believe is that we need to do a better job of really communicating to people, to local communities, about why data centers are something that can be beneficial to them. And you know, I grew up outside of a town, Grand Forks, North Dakota, where we had a sugar beet factory. And by the way, the sugar beet factory smells incredibly bad. Like you don't want to live right next door to it. But it was really a staple of the town. And I think it was something that had created a lot of jobs. So it's kind of in many ways the centerpiece of the community. And I think that helping people understand not just that data centers, the investment, the community benefits, for example, in Georgia that we're sponsoring free lunches for students, that all of that is beneficial, but even the output, right, like the AI technology is also something that is important for them, for their lives. And I think that all of that, communicating it and really substantively living that, is something that we need to do a great job of.

Well, I think I don't think there's anyone who could say that they were not surprised by that. Like I think that it is definitely an issue that's very singular and no one's really seen something like it in American politics. And in some ways though, again, I step back and really think about the part that we can play, like what difference can we make, and that a lot of our shift over the course of this year has really been to realize that from San Francisco trying to build infrastructure in Texas and Georgia and other places, you can't just tweet and say like this is going to be good. You need to be in those communities. And some of the most effective programs that we've run have been when our teams are there on the ground and stay, right, don't show up for a week, go back to San Francisco, but are there and really continue to show up. And so to me, I think that there is something that we have been learning, and again, I think we need to do even better, and we intend to do so.

Well, my view again to really zoom out is that we as a society, as an industry, have never prioritized security the way that it should. Like when was the last time that a CISO was overresourced? And I think we all kind of know the internet wasn't built for security, right? That security was added on. You think about the history of trying to even add encryption to, you know, to HTTPS, to the internet. That was a retrofit. It wasn't how the internet was designed. And so I think we now have 40-ish years of tech debt that has been building, building, building. And AI in some ways is almost like shining a light into the cracks that we have all created. And I think that what AI can do is that we have this opportunity to put the best AI in the hands of defenders so that defenders can get ahead and actually close those gaps and actually secure the internet in a way that it's never been before. And that's something we call the defenders' window, this advantage that the defenders have over the attackers. And so I do think that we need to build in a different way, in a more secure way, in a safe way. But I think we can move from a world where breaches are just a thing that happens to one where that's just unthinkable, right? That you have real security guarantees, formally verified code, and code that was written in the first place to be secure by models that are just far better than people are at producing that kind of guarantee.

So, this is something that first of all, it's a very controversial concept, but it's also we're not the first people to propose it. I think as you really think about a world that we're heading towards where there are going to be more vulnerabilities found, and that every company, every organization needs to increase their rate of patching. And you can just see many companies have like a quarterly patch cadence. That is just not going to cut it anymore, right? People need to bring it down to a month, to a week, to a day, to an hour, to a minute. And I think that that change, it's possible. We have the technology and the tools to make it possible, but it really is going to require collective action. And so if you're in a position where people aren't patching, where people do have servers that can be attacked, then you have a question of is there someone who can help prevent that from turning into big botnets that are then causing damage to others. And I think to this question of well, if you do have vulnerabilities, then the government could use the vulnerability to get in and apply the patch themselves. But again, it's controversial for a reason, right? It's a little bit like well, the server, it's possible you'd have some other side effects, right? It's possible you'd actually take down the service. And so I think that this needs to have some really delicate thought, but it's not without precedent. For example, the FBI over the past five-ish years, I think has three or four times gotten court orders to go and clear out malicious botnet software from private infrastructure. So hundreds of thousands of computers, the FBI goes in and actually clears out this malicious code. So it's the kind of thing that has happened, and I think it's really just saying, okay, we see what's coming, we see the shape of these vulnerabilities emerging, and how do we get ahead of that and have a structure that really keeps the internet safe, secure for all of us.

I think we've started to kind of float this idea, and I'd say it's again, this is not the only idea possibly on the table, but we definitely have been engaging very well with the government on cybersecurity, on the vulnerabilities. PHP, for example, we talked to not just the US government, we talked to many other governments around the world to give them advanced notice so that they could prepare, and that we've been starting to tell them it's not just this one vulnerability, but this whole sort of mode that we're going to be in for the next six, twelve, eighteen months. And I think that we collectively as society need to respond differently to it from really any period before.

Well, first of all, I think we have an incredible team at OpenAI, and working with them is just one of the best privileges of the job. One of the things that I have found, and maybe the core theme I've brought to each of these functions as we've started to bring them together, is code design is really thinking about the end-to-end. You can't just think of any of these functions in isolation because what AI is is changing, right? The research, every year we have a new model that obsoletes everything we've done before, and you can see this with just the advances consistently across different modalities, across individual functions like software engineering, totally different today from what it was at this conference last year, and before then it was barely touched by AI, right? Like that's what's really happened in this time. And so of course you can't just have an isolated product organization that doesn't talk to research, that makes no sense. And I think the same is true for every function. So to me, one of the sort of easiest and also most high-leveraged things I've been able to do is just provide this cross-connectivity, this connective tissue, and say, hey, on the marketing side, this is kind of what we're seeing coming on the research side, so we should think ahead three steps to this is where we're going to be, let's start messaging ahead for that so people can understand it. And so I think that this just like really trying to have a through-line to everything we're doing, make it simpler and more streamlined in a single direction. Just that's the general theme that I think has really yielded a lot of the fruits that we've seen this year.

So I think to me this became fairly clear, like honestly, even at the very beginning of the year. And I think that if you look at what's really changed this year, Q1 was pretty rough. Q2 was pretty rough. It really looked in many ways like coding. We weren't even in the conversation, right? We had Codex, but no one was talking about it. And I think that we just kept our heads down, focused, and executed. And Q3, entirely different, right? We had 70% quarterly growth in our annualized revenue. And if you just break it down by the enterprise side, doubling, right? Like that's like crazy growth for a single quarter. And that it wasn't an accident. It wasn't something we did in that quarter. It was all the investments that we'd been making up to that date. And so we got a frontier model out in the form of GPT-5.6 Sol. We got ChatGPT Work released as well. And there had been all this sort of painful behind-the-scenes work that resulted in this incredible revenue inflection.

I think that selling to enterprise is, first of all, you just hear so much from every single conversation. Like maybe the single biggest surprise that I've had is how every single customer meeting that I have, every time that you're talking to almost anyone, regardless of if it's a CEO, developer, salesperson, it doesn't matter, that there's always some insight in there that I have this aha moment, right? In this like, wait, I've never really heard anyone say it this way before. And so I think that there's all of this kind of, it's like the elephant problem of everyone's touching a slightly different part of it, and you realize that transforming an enterprise and really delivering value, everyone is doing their part. And I think that a lot of our job is to figure out how do we actually help you figure out what are the most important milestones that can be achieved with our technology, how do we show up for you consistently as a partner, how do we build trust and build these relationships and ensure that you as an enterprise know that we're here for the long haul and are a reliable partner. And so I think systematizing how we sell has been a very important part of what we've done. And if you think about where we were a year ago, we weren't even really in the enterprise game, right? We were really perceived as a consumer company, and a lot of the companies we'd start talking to would say, is OpenAI really committed to the enterprise? But it's so different today. And I think that is due to this continuous investment and the way that we show up to our customers every day.

Well, so within the company we were probably, I don't know, like I think our enterprise revenue was about 30% versus consumer at 70%. And now we're probably somewhere around like we're majority enterprise. And it's not that consumers shrank, right? It's been growing, but it's the enterprise segment has really taken off. And so I don't know exactly how to quantify in the broader market, but you can see the way that we're winning deals. So for example, actually one that's hot off the press, has not been previously announced, is that we just papered a partnership with JPMorgan Chase, and that they're going to be using Codex. They're going to be using our cyber models to secure themselves, deploying our models for enterprise transformation, knowledge work across the company. And that for me is like such an iconic institution in such an important domain, right? A highly regulated enterprise that trust is like so key to what they do, and that they chose us, and that we're here to be a great partner.

I think so. Yes. I mean, look, the way I put it is that we've been very clear this year that we want to go public when we feel is the right time for us. And I feel extremely good about the business. I feel like we've made so much progress this year, and I've honestly never felt more confident in what we're doing.

Well, look, I would look at, I mean, to me, just at a qualitative sense, like if you look at what's really going on in these models, is that we have been able to make these incredible efficiency gains very repeatedly year after year. For example, we dropped the price of Luna 80%, like an 80% price cut this year, and I think that our historical average has been that for a fixed level of intelligence we probably do a 10x or even sometimes almost 100x price cut year-over-year on it. And I think that you can look at that from two ways. Like one is that you can just keep some of that margin, and the other is you can just say that these models, you can get such incredible efficiencies. And so my view of where we're headed is a world where the frontier models, and you can just see this even for looking at like OpenRouter stats and these other publicly available ones, is all of the dollars basically go to the frontier models, and then you have these lower-margin but extremely high token count models in the form of things like Luna. And I think that the margins basically, people are almost price-insensitive sometimes to an irrational degree on the frontier models, like people just like, give me the best thing. And I think it also shows you how much value these are delivering, right, for customers, certainly in many industries, that if you give them the smartest possible model, that they can make incredible revenues out of that. And so you almost can tune your margins almost arbitrarily there. And so to me, I think that the opportunity and kind of the engine and the pace of progress, all of that is kind of coming together in a way that I think that you'll just continue to see these numbers skyrocket.