Enterprise AI

“Because enterprise AI particularly, you're not going to be on the 20 dollar plan. You're not going to be on the 200 dollar plan. You're going to be consumption based. And you're going to look at it a lot more like a marketing line item that's proportional to y…”

“We understood that there's a problem with how this works because we have different incentives. You were tasked with doing that. I'm tasked with making sure my systems work, and I'm tasked with making sure that data is intact, no data is running away. I don't a…”

“Now it seems that you're coming to a large legacy enterprise. They really want to adopt the ad because they have to, the problem is they don't know how to do it. They understand that their processes are very long. There's something that takes a year or two or …”

“If you are using AI for something really important, ask yourself, who is checking the outputs? And the information that you're getting. And if it's the company that sold you the AI, you have a problem. So you, whether you're building your own evals internally …”

“Generally in these conversations, we're not really having to convince people to like, Invest in this space. It's, like, more of, hey, we're the right approach for you, so you can partner with us.”

“Again, working in enterprise AI for a company that is only focused on enterprise AI since its founding, you see how that energy distorts the proper conversation very quickly when open AI comes in. Like suddenly the way people approach it, the scale with which …”

“I don't think there's an ROI problem right now. I think we're in a period of exploration and experimentation where there's more tolerance, more patience To get that ROI calculation right now.”

“I really see people will own their, every single company will own their own intelligence as a must-have. It's not optional.”

“We are absolutely in a land grab, like, you know, no question. Like every single company in the world wants a product like ours today. And either we get in today or it's going to be like 10 times harder to actually get in the future.”

“I think this is going to fail because I don't think there is enough talent To do what we want to do in the enterprise. The idea makes sense to on a spreadsheet. It makes sense. Sad is smarter than me, but I, my today, my experience is it's going to fail with a…”

“On the enterprise side, false positives matter a lot. They matter because if you imagine a future where an agent's going to make independent decisions and act on it, you have zero tolerance for false positives.”

“The real enterprise revenue is going to come from use cases that are required a lot more context.”

“The models are capable of so much more, but humans are still not extracting the fullest value from these models, especially in enterprise. In enterprise, I think first mile at last mile is still a problem.”

“So at some point, you're going to start seeing front page headlines in the Wall Street Journal saying, this healthcare company or insurance company rejected one million claims, which it shouldn't have because the AI agent went rogue, or this credit card compan…”

“I would say enterprises don't optimize for accuracy of a model, right? So they're more so optimizing for reliability and trust. So it's very it's very, I think, in today's age with this new, ah, level of capability that the models have, getting the accuracy ri…”

“You're gonna go from 10 bips to one, to two or three percent, to five percent, to 15% in the next four years”

“These things become competitive necessities, and everybody has to buy it and use it. But the cost saving or the productivity gain that you get from it just kind of gets competed away, so you don't get to charge more for it.”

“I think we're going to see a pullback and we are going to recognize, but structurally, I mean, this is the thing structurally, when you go to your entire engineering team and say, Go use as much as you can of this when there's no clear direction.”

“AI is very, very underpenetrated. It's probably around one percent penetrated in terms of real enterprise AI use cases”

“My prediction is that we're living in the age of enterprise AI. And I think in the next 12 to 24 months, you're going to see the beginning of a consumer AI renaissance.”

“Companies really need not just some training and education and show them what to do. They need somebody that is embedded into their company that is following up regularly and becoming part of that company.”

“Enterprise is two thirds of the ball game in AI and consumer is one third or less, which is the flip of the last time.”

“Today, I don't think customers are getting, like, in general, as people have been embracing AI, they aren't getting that level of exponential output or maybe the right way to say it is they aren't getting the level of exponential outcomes from their investment…”

“I think right now the ability to absorb and adopt the tools is going to be the limiting factor for years to come.”

“So I think last year, enterprise AI had about thirty seven billion of total TAM and it's continuing to grow like crazy”

“On Prem is back. It's going to happen. It's gonna happen.”

“What we see in enterprise is rarely things that are solved with agents because that's not necessarily where you would expect an FDE to be most useful. Where there is more values, value is in more complex workflows where you will have several agents interact th…”

“In reality, paying customers want like a good trade-off in terms of performance for efficiency. So, you know, we'll train bigger models, but we'll deploy smaller models because it gives us that trade-off. It's like good enough intelligence to get the job done.”

“On the enterprise, I think things are going to keep going, and especially Cogen. I think we are not going to see a plateau in Cogen. I think that is going to get much better really, really fast.”

“We're never going to be able to build systems that work out of the box in a single shot. And the one thing that we try to convey to our customers is that they need to build a prototype that's going to work 80% of the time. But then how do they get from 80% to …”

“If you're building something where the hardest part is getting adoption and workflow embedding, and you need to actually change the way a company works, then yes, forward deployed engineers are the only way to do it.”

“The thing that I feel you know, is happening in enterprises, you hear these 95% of projects fail, But, like, you know, like, that's actually what you want. Like, you, like, when you are actually experimenting with new technology, if all of your projects are fa…”

“It really comes down to your company. What data does your company have that's special? That your competitors don't have. Can you leverage that? And can you build AI that really understands that data? Because that's not a commodity. There's not an AI out there …”

“It's expected, according to Gartner, to bring in 37.5 billion dollars in revenue next year. Enterprise AI. That's up from zero in 2022 or effectively zero in 2022.”

“There's like, seven hundred billion dollars being spent in enterprise AI. It's growing very, very quickly. It's gonna keep growing quickly.”

“Organizing the data layer turns out to be probably the most complicated thing which spans the enterprise such that it can meet the intelligence”

“It's only valuable to train on our own internal context, A, and B, that model does not have to have read War and Peace to deliver to us that it doesn't have to be generally trained on everything that's available. It has to be trained on our content. And so the…”

“When you need to sell AI to a business, you get a real signal of what works, what doesn't work. And you know, we've been using these academic benchmarks for many years. You get some signal, but it's not the same as getting this to do productive work.”

“I think that this next generation wave of change will come. It will take a while, and it will be a slow, a slower than expected adoption on this complex side while the easy cases will be solved quite fast, very fast.”

“It'll probably probably be a smaller model. Oftentimes we see a half a billion to a ten billion parameter model. That's the regime, not a trillion parameter model. And this will be faster, more accurate.”

“Basically what happens is the POCs Get to, like, 60 or 70% of the way there, and the human mind goes, oh, the rest is no big deal. But it's kind of like uptime in data centers where, like, every nine is, like, you know, an order of magnitude investment, you kn…”

“If you have engineers who've worked with models before and they put in the time and I'm talking about like months, not like minutes, like you see on these videos to actually get legal approval, policy approval, regulatory approval change management, like an ac…”

“That's because the industry is changing a lot. Every day, ah, it changes, you know, GPT-V comes out, and it's different than, you know, it was three months ago, and so what we need to actually build in product changes, and so we've just said, you know what, th…”

“In many ways, I always kind of say we haven't yet seen the ChatGPT moment, I think, in business for AI.”

“Well, no, so I'm a firm believer that no, no one is going to win it all. The consumer and enterprise are different, that different, you know, like the act of software engineering is different than the act of marketing. And I'm definitely not a God model. One m…”

“And that, that's something where I do think We have to be prepared for this as many years. It's about the speed at which humans can change their workflows as opposed to how kind of quickly the technology can just, you know, sort of evolve in advance.”

“In the ideal spirit, we see employees as orchestrators of workflows in enterprises, and this will drive the next generation of productivity improvements.”

“On the other hand, think about like a medical treatment planning or venture capital or legal strategy, right? Those are the things where the tasks are quite complex and you require High human judgment. Even there, AI can be deployed, but the way you deploy it …”

“So I think in general what we have seen is enterprises are fine using AIs as long as we show them predictability. They don't care about, you know, 99% accuracy. You can be 90% accurate or even 80% accurate, But just tell us which 20% need to be reviewed or whi…”

“So there's that phase of like POC or figuring things out. It feels like it's passed us by now. Like most organizations know the opportunity. They know what they want to do, and they really just need help to go execute on it.”

“But when you were going into kind of 24, less than 10% actually moved into production. All of the, all this AI experimentation that was funded by, you know, innovation dollars that Were kind of limited, but didn't really create believers. And from 24 till the …”

“Palantir is re-accelerating at an incredible rate at three and a half billion in revenue, all driven by enterprise AI deals.”

“I don't see the disillusionment. I don't know where this is coming from. I don't even think we're at the peak yet.”

“Most of these pilots are very much intended to be churned. Like, they're not, they're very much in a, they're not being rolled out broadly. They are coming through in a kind of walled off environment for people who are, like, gonna be the beta testers.”

“So, so this is the part that will take years to fully figure out and get right.”

“On the enterprise side, I absolutely see there being all kinds of specializations because so far in whatever the last 50 years, it's not the case that there's been an equivalent of Google search.”

“And although, yeah, 80% failure rate is not uncommon or call it, you know, getting thrown on the shelf, right? First of a kind is last of a kind type of scenario.”

“And we often find many of the POCs turn into, they don't require complex AI, new model development and things in that space. They require simple automation. So they require more or more data, right? Or more programmatic changes in how the application is operat…”

“And I think in twenty-twenty-five, going back to your first question, we'll make some pretty material advances there, where the predictability is much better, and that will lead into, I think, twenty-twenty-six, where we'll start to see pretty significant ROI …”

“I think, like, 90% of enterprise AI right now is almost like this vapor where, hey, we swear it works, like, look at this amazing demo where we ask, What does the CEO say about the investment? And the minute that they actually go to, you know, try to use it in…”