In August, Ghodsi told the Wall Street Journal that he believed Databricks, which is reportedly in talks to raise funding at a $134 billion valuation, had “a shot to be a trillion-dollar company.” At the Fortune Brainstorm AI conference in San Francisco on Tuesday, he explained how it would happen, laying out a “trifecta” of growth areas to ignite the company’s next leg of growth.

The first is entering the transactional database market, the traditional territory of large enterprise players like Oracle, which Ghodsi said has remained largely “the same for 40 years.” Earlier this year, Databricks launched a link-based offering called Lakebase, an operational database optimized for AI agents, in an attempt to capture some of this market.

The company is also seeing growth driven by the rise of AI-powered coding. “Over 80% of the databases that are being launched on Databricks are not being launched by humans, but by AI agents,” Ghodsi said. As developers use AI tools for “vibe coding”—rapidly building software with natural language commands—those applications automatically need databases, and Ghodsi said they’re defaulting to Databricks’ platform.

“That’s just a huge growth factor for us. I think if we just did that, we could maybe get all the way to a trillion,” he said.

The second growth area is Agent Bricks, Databricks’ platform for building AI agents that work with proprietary enterprise data.

“It’s a commodity now to have AI that has general knowledge,” Ghodsi said, but “it’s very elusive to get AI that really works and understands that proprietary data that’s inside enterprise.” He pointed to the Royal Bank of Canada, which built AI agents for equity research analysts, as an example. Ghodsi said these agents were able to automatically gather earnings calls and company information to assemble research reports, reducing “many days’ worth of work down to minutes.”

And finally, the third piece to Ghodsi’s puzzle involves building applications on top of this infrastructure, with developers using AI tools to quickly build applications that run on Lakebase and which are then powered by AI agents. “To get the trifecta is also to have apps on top of this. Now you have apps that are vibe coded with the database, Lakebase, and with agents,” Ghodsi said. “Those are three new vectors for us.”

Ghodsi did not provide a time frame for attaining the trillion-dollar goal. Currently, only a handful of companies have achieved the milestone, all of them as publicly traded companies. In the tech industry, only tech giants like Apple, Microsoft, Nvidia, Alphabet, Amazon, and Meta have managed to cross the trillion-dollar threshold.

To reach this level would require Databricks, which is widely expected to go public sometime in early 2026, to grow its valuation roughly sevenfold from its current reported level. Part of this journey will likely also include the expected IPO, Ghodsi said.

“There are huge advantages and pros and cons. That’s why we’re not super religious about it,” Ghodsi said when asked about a potential IPO. “We will go public at some point. But to us, it’s not a really big deal.”

Could the company IPO next year? Maybe, replied Ghodsi.