Cofounder and CEO, Databricks
Databricks CEO Ali Ghodsi: AI doesn't have an intelligence problem. It has a context problem
CNBC's Jim Cramer speaks to Ali Ghodsi, co-founder and CEO of Databricks, to break down the company's fundraising and efforts to improve artificial intelligence.
About Ali Ghodsi
Ali Ghodsi, cofounder and CEO of Databricks, has been speaking publicly about the company’s recent fundraising, product launches, and his views on the state of artificial intelligence. In July 2026, Ghodsi said on CNBC that Databricks was fundraising at a $188 billion valuation, driven by customer demand for open-source AI models such as Kimi and a resulting shortage of GPUs. He stated that the company’s Unity AI Gateway product, which allows customers to use both open-source and proprietary models, had seen explosive demand. At the company’s Data + AI Summit in June, Ghodsi announced the open-sourcing of a new project called Open Sharing, which he described as a superset of Delta Sharing that enables sharing of data, AI agents, skills, and models. He also noted that over 100,000 people had signed up for the event, making it the largest data and AI conference in the world. Ghodsi has repeatedly argued that artificial general intelligence (AGI) has already been achieved, stating that the current constraint on AI productivity is not intelligence but context. He said that AI models are already smart enough but lack the enterprise context—such as data, processes, and organizational knowledge—to be fully useful in the workplace. He described Databricks’ Lakehouse as a “system of record for agents” and highlighted new products including Customer Lake for marketing and Lake Watch for security. On the topic of an initial public offering, Ghodsi said he believes 2026 is a “terrible year” to go public due to macroeconomic uncertainty and the presence of several large IPOs, and that Databricks, which he said does not burn capital, can afford to wait for more stable conditions. He also noted that the company may raise additional private capital before going public.
Transcript (17 segments)
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Jim Cramer0:09
If you want to get a read on AI, it's not enough to follow publicly traded companies, because many of the most important players in this space are still private. Take Databricks, which helps companies take messy, fragmented data, organize it, analyze it, build AI on top of it, and frankly, figure out what you have. As of February, this company had $5.4 billion annual revenue run rate, and by now it's got to be substantially higher than that, as these guys are growing like a weed. Databricks is free cash flow positive. It's bringing in tons of business. There's a reason this company got $134 billion valuation in its last private fundraising round. All that helped send Databricks to the number three spot on this year's CNBC Disruptor 50 list. Now that AI has entered the agentic era, this one's become a heavy hitter. So let's take a closer look with Ali Ghodsi. He's the co-founder and CEO of Databricks. To learn more, Mr. Ghodsi, welcome back to Mad Money.
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Ali Ghodsi0:59
Thank you so much. Always great to be on.
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Jim Cramer1:01
Hey, it's great to see you. First of all, I got to go through this rigmarole. I'm sorry, but, you know, we got all these people, you know. When is Anthropic going to come? OpenAI, is it filed at SpaceX? A lot of those companies need money. When I look at your company, I say to myself, here's someone who's in the driver's seat who can come public, not come public. Is that not a better way to look at Databricks than the other guys, where we play the guessing game all the time?
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Ali Ghodsi1:26
Yeah. I mean, the way you think about it is that if you're burning huge amounts of capital like ten, 20, 30, $40 billion, you need the capital, you need to be in the public markets. You have no choice. For Databricks, we don't burn any money at all, $0. So for us, we can choose the timing. I think this is a good year to be private, because I think this is a good year where you want to be building, because we're going through a huge transition in the market, in public, in private, all enterprises. This AI revolution is happening. So it's better to build in private right now. And we will be public and we will go public. But I don't think this year is a good time for us.
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Jim Cramer2:02
All right. So when I first met you, I said, well, wait a second. I see what's going on here. You can take the data, but it's your data. You can prosecute it. You can ask the question, you can inquire things. It seems like ever since AI, now there's like 100 things you could do if there were five things before. Do you advise your clients, look, you can do this now. And do they avail themselves of it?
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Ali Ghodsi2:23
Yeah. Look, I think the thing that is top of mind right now for every CEO on the planet, not just in tech, any CEO is, wow, these AIs are so amazing. They can do so amazing things, but secretly, and they don't want to admit this, my organization has none of the AI. It's not established. We don't have agentic coworkers doing lots and lots of work. How do I get AI into my organization? And they have plenty of intelligence in the AIs. But why are the agents not working in the enterprise? What's going on? And the simple answer to that is the AI is, if you give them all the data and the context, if you perfectly ask the question with all the context, they will nail the answer every time. So the big question is, AI doesn't have an intelligence problem. AI has a context problem. How do we feed it that context? And that context is in the data. So that's top of mind. Everyone wants to solve this problem. That no one on the planet right now doesn't want to have this problem nailed.
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Jim Cramer3:16
All right, so how about if I had Genie, what would I do with it?
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Ali Ghodsi3:21
Yeah. So Genie has built into it something called Genie Ontology.
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Jim Cramer3:25
So Genie Ontology. So you're talking, that's what Palantir taught me with the word ontology.
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Ali Ghodsi3:31
Yeah, they have it too. And they're a great partner. But the way Genie Ontology works is that it automatically, we already have all the data in what we call the Databricks Lakehouse. That data is sitting there, but it's a lot of data, structured, unstructured. So we don't want to have the AI just go loop through the code and just loop through all the data and search for nuggets. That's what happens today. Today, people use a cloud code or use some other agent, and it just goes through and loops through. Costs a lot of money to loop through all the data. So what we do is we automatically in Genie have constructed the graph. So ontology is a graph and it has these little snippets of nuggets of information. Like, you know, revenue is calculated this way. Number of employees is found over there. Product categories is here. And when you ask a question, it uses this ontology inside Genie to answer those questions. So I personally, every meeting I'm at, I'm using Genie. Like anything that comes up, I'm asking the question in Genie. It's giving me the answers. A lot of the things that otherwise I would have to wait two or three days or have someone go look up the numbers. Because you know, you really want numeracy and you want analytical quantitative accuracy here, right? This is not about producing text. You want it to produce for you, what are the different revenue categories. And you want those numbers to be accurate. So Genie really excels at that. And a lot of that is thanks to this ontology graph.
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Jim Cramer4:43
Okay, so tell me, let's say I'm with another outfit, we've had Snowflake on many times and I hear what you said and it sounds like, wow, you guys are doing some cool stuff. Isn't it too costly to go from Snowflake to Databricks?
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Ali Ghodsi4:57
Well, I think that's a great company. You know, the two companies have different backgrounds. We grew up in AI, so we started doing AI, you know, in 2009, frankly. And then when the company started 2013, we're at this point synonymous with the data and AI company. If you search for that, it'll come up Databricks. You know, their roots are data warehousing, but they're great. They have a great CEO and they're moving fast. And, you know, they're adding AI capabilities as well. So, you know, there's competition in the market. I think the Genie Ontology is special though. And I think our open approach to data is also unique and very differentiated from all the other vendors. We started this whole revolution by data should be open in open formats. It should be in one place, what we call the Lakehouse. That turns out that's really important for the agentic revolution because you can't grant access for each of your proprietary siloed databases to your agents. The agents just go to this Lakehouse. So the Lakehouse has become the system of record nowadays. So I joke and I call it SORA, you know, the system of record for agents. You know, that product name is now available. So, well, that's what we call it.
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Jim Cramer6:01
Last question. I am confused about this. What's the proposition to stay off of your product? I mean, if I meet a CEO and they have all their data on-prem and they can't prosecute it using Databricks, shouldn't I make a presumption that perhaps they are old school and not availing themselves of things that would make them more efficient and better at what they do?
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Ali Ghodsi6:26
Yeah. I mean, all of these guys want to move to the cloud. First of all, the vast majority of Fortune 500, Global 2000 already for the core workloads are in the cloud, but especially because, you know, the GPUs and the AI in the cloud. But yeah, some are locked down on-premise and we're working with them. They want to get out. I haven't heard anyone that says, hey, we're on-prem. We love it. We're going to stay there. Much better. The GPUs are better. The AI is better. Leave us alone. You're wrong. Nobody's, I don't know anyone.
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Jim Cramer6:49
I don't know how if I were running a business, well, actually, I've run a couple businesses. But if I were running a database business, of which currently I am aware of one, how I would do it without you. Because everything's guessing, right? We would just use the old way we used to guess. We would look at some things. Maybe we have a focus group, maybe we pick a couple of accounts, see what's going on. But isn't that the way it used to be before Databricks?
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Ali Ghodsi7:13
Yeah. I wouldn't say we are the only company that actually enabled that. But yeah, this is, I mean, the AI revolution with data is happening. It's what's enabling that. The key missing piece though, is that context. How do you get that context and that data into the agents? And I think that's far from a solved problem even by us. Right? But yes, we're seeing it. Like, you know, one of my favorite examples is Prada. Everyone knows the brand Prada, and they used to have all the revenue, all their KPIs, all of this in Excel, in spreadsheets. And so they moved it into our lake-based database that we have. And then now they can, with AI in real time ask questions. You know, who's buying a purse, you know, who's buying a shoe or, you know, tell us about their inventory and so on. So yeah, now we can do it with AI and, you know, it just is magical.
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Jim Cramer7:55
Well, I think it's great to have you on. It's magical to have you on because you speak English and you get the job done. And it's a joy to have you because, you know, it's great. A guy who's trying to figure out what's right for the business is often very different from a guy who's trying to game the stock market. And we know many people are trying to do that now. Ali Ghodsi is co-founder and CEO of Databricks. This is number three of Disruptor list, but it's probably one of, I don't know, I shouldn't slander all the other companies, but this is the one that doesn't need to come public. That's the kind of company you really want. Thank you. Great to see you.