Artificial intelligence can cut hours off financial modeling and scenario planning, but finance chiefs who let employees use it without clear guardrails are taking on risk they can't see. CFOs need formal processes around AI governance and ethics before the technology becomes embedded in how their teams build models, according to Ian Schnoor, executive director of the Financial Modeling Institute.
Schnoor told CFO Dive that many companies are still in the early days of adopting AI and "do not have strong disclosures or guidelines yet around AI." That's a problem, he said, because finance leaders need to know exactly how the technology was used in any process that feeds into their decisions.
"But if I was a CFO, I would want a policy to know exactly, how was AI used in this process?" he said.
AI 'time zero' in financial modeling
Schnoor, who started his career as an investment banker at Citibank and has led the Toronto-based FMI since 2016, dates AI's "time zero" for financial modeling to around February. That's when the technology first showed a legitimate capacity to build models on its own.
The immediate reaction in the industry was nervousness that modeling skills were about to become obsolete. A few months later, that flipped. The realization set in that "people probably need stronger modeling skills than they ever needed before" in the age of AI, Schnoor said.
Part of that shift came from a simple truth: AI doesn't inspire the trust of a human analyst. Company leadership still wants a subject matter expert who knows the ins and outs of the model. "At the end of the day, the trust and the confidence comes from a human delivering a message to another human," Schnoor said.
Building the governance framework
For CFOs, transparency is not optional. They carry ultimate responsibility for their businesses' financial decisions and the corporate strategies that follow. Schnoor said the first priority should be a strong framework around AI usage on the finance team - one that covers not just how AI was used to develop a model, but what employees actually did in the process.
"First, tell me how much AI was used, but second, tell me what human interaction did the team do?" he said.
He also advises CFOs to spend time experimenting with AI themselves in the early days, running their own checks and stress tests on models. The stakes are too high to delegate that scrutiny entirely.
"At least in these very early AI days, I probably need to kind of dive a little deeper than I normally would, just to make sure that nothing's going to fall through the cracks because we're still developing processes and systems, and I can't risk an error built by an AI agent," he said.
Human judgment has to stay connected to decision-making and inputs as AI usage grows. AI can speed up manual processes attached to models, Schnoor said, but "we cannot allow AI to arbitrarily choose inflation rates, interest rates, cost assumptions without having massive insight and oversight into what that means."
For finance professionals looking to build these capabilities, structured training can help. AI for CFOs covers the governance and ethics considerations finance chiefs need to address, while broader AI for Finance resources focus on practical applications in modeling and analysis.
Why this matters for finance professionals
The CFO who adopts AI without a disclosure policy is making a bet with someone else's money. Every model built with AI assistance carries hidden assumptions - inflation rates, interest rates, cost projections - that the finance team must be able to explain and defend. Building that capability now, while the technology is still new, is what separates a team that uses AI as a tool from one that gets blindsided by it.
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