“AI can build models and run analysis and create reports much faster and much better than any human,” Didi Gurfinkel, the company’s cofounder and CEO, told Fortune in an interview. “So all these tools that focused on creating tools for people, for humans—they’re not relevant anymore. The opposite. They limit the AI.”
But the arrival of generative AI, Gurfinkel said, has changed what’s possible—and what’s needed. AI models can generate sophisticated financial analyses in seconds, but chief financial officers can’t simply throw their data into ChatGPT or Claude and trust the output.
“The one challenge or problem that currently CFOs have with AI is trust,” Gurfinkel said. He breaks this into two dimensions: trusting the data the AI is working with and trusting that the AI’s output is repeatable. The latter is especially challenging since the leading AI models are inherently probabilistic and won’t give the exact same answer to the same prompt every time.
Then, once a financial model is built with AI, FinanceOS allows a customer to lock that model in place so that the finance model remains consistent, while the underlying data refreshes each period.
At a time when investors are hyper-focused on how AI challenges the traditional license payment per user business model from software-as-a-service vendors, Datarails is leaning into disruption. It’s shifting to a usage-based pricing model, which Gurfinkel said makes sense as AI agents, not humans, are increasingly using software.
“Total spend on software will be higher—it will increase,” he said. “But probably the number of people will be less. AI can do more. So if you take this equation, you get to one very obvious conclusion: the CFO will pay by the value.” Gurfinkel said that usage-based pricing is a proxy for the value a company derives from using a product.
Gurfinkel was blunt about the competitive landscape, arguing that many of the industry’s oldest FP&A software vendors are in trouble. “They’re already gone. They are slow. They don’t have enough cash or energy to rewrite the technology,” he said. Newer entrants such as Abacum and Runway, which invested heavily in sophisticated web interfaces and algorithmic workflows, face a different challenge: They need to reinvent themselves after underinvesting in the data consolidation layer that Gurfinkel believes is the new strategic high ground.
The good news for those companies, he said, is that most have recently raised significant capital, giving them time to adapt. “But it will be interesting to see how they react to this change,” he added.
He draws a parallel between what he predicts will happen to financial professionals and what is already happening in software engineering, where AI coding assistants have transformed how developers work. “You don’t see any programmer that actually types on their keyboard,” he said. “Almost 100% of their code is written by AI. And I’m confident that it will be exactly the same for finance people.”
Datarails said FinanceOS is available immediately and can be fully operational within a few business days, the company says. Datarails’ existing FP&A, cash management, month-end close, and spend control products remain available as managed solutions built on the same underlying platform.
