On Monday, Databricks revealed it has achieved a $5.4 billion annual revenue run-rate, marking 65% year-over-year growth. More than $1.4 billion of that total came from its AI product portfolio.

The broader question for the industry is what becomes of all these companies and what AI will ultimately do to them. For Databricks, the effect is straightforward: "For us, it’s just increasing the usage," the company's CEO noted. He is also keen to shift the perception of Databricks away from the traditional SaaS label, as private markets increasingly value it as an AI-centric company.

Also on Monday, Databricks formally completed its previously announced massive $5 billion funding round, which values the company at $134 billion. The company additionally secured a $2 billion loan facility.

Databricks continues to operate in two spheres. It remains widely recognized as a leading cloud data warehouse provider—a critical system where enterprises consolidate vast amounts of data for business analytics. The CEO highlighted one AI product in particular that is boosting usage of its data warehouse: an LLM-powered interface called Genie.

Genie exemplifies how a SaaS business might replace a conventional interface with natural language. For example, the CEO uses it to ask why data warehouse usage and revenue surge on specific days. Just a few years ago, such a question would have required specialized query language or a custom-built report. Now, any product featuring an LLM interface can be used by anyone, he pointed out. Genie is a significant factor behind the company's rising usage metrics, he added.

The risk AI poses to SaaS is not, as one AI investor humorously suggested, that companies will tear out their essential "systems of record" to install makeshift, AI-generated replacements. These systems store vital operational data across sales, support, and finance. "Why would you move your system of record. You know, it’s hard to move it," the CEO reasoned. Besides, AI model developers are not offering databases to store that data and become systems of record themselves.

Instead, the transformation lies in replacing the user interface—either with natural language for human users or with APIs and plugins for AI agents. Consequently, the threat to SaaS businesses, he explains, is that professionals will no longer dedicate years to mastering a specific platform like Salesforce, ServiceNow, or SAP. Once the interface becomes simple language, the underlying product becomes as invisible as plumbing. "Millions of people around the world got trained on those user interfaces. And so that was the biggest moat that those businesses have," he cautioned.

SaaS companies that adopt the new LLM interface can expand, much as Databricks is doing. However, this shift also creates opportunities for AI-native competitors to offer alternatives better suited for AI and autonomous agents. This is precisely why Databricks developed Lakebase, a database designed specifically for AI agents.

Early adoption has been promising. "In its eight months that we’ve had it in the market, it’s done twice as much revenue as our data warehouse had when it was eight months old. Okay, obviously, that’s like comparing toddlers," the CEO remarked. "But this is a toddler that’s twice as big."

With its latest substantial funding round now closed, the CEO confirmed the company is not actively planning another raise or preparing for an IPO in the immediate future. "Now is not a great time to go public," he stated. His priority was to ensure the company is "really well capitalized" in case market conditions deteriorate again, similar to the post-ZIRP downturn in 2022. A robust balance sheet "protects us, gives us many, many years of runway," he added.