CFOs need AI governance frameworks before disclosure gaps widen

CFOs need AI governance frameworks before disclosure gaps widen

As artificial intelligence becomes embedded in financial modeling and scenario planning, most companies lack the disclosure policies and governance structures needed to manage the technology responsibly, according to Ian Schnoor, executive director of the Financial Modeling Institute.

The gap is particularly concerning because finance chiefs bear ultimate responsibility for financial decisions and corporate strategies built on AI-assisted models. "If I was a CFO, I would want a policy to know exactly, how was AI used in this process?" Schnoor told CFO Dive. Yet many organizations "do not have strong disclosures or guidelines yet around AI."

Why it matters

Without clear governance frameworks, CFOs risk making critical business decisions based on models they don't fully understand. As AI adoption accelerates in finance functions, the window for establishing transparent processes and accountability structures is narrowing. The stakes are high: errors in AI-generated financial models could lead to flawed strategic decisions, compliance issues, or loss of stakeholder confidence.

From replacement fears to skills imperative

The financial modeling industry reached what Schnoor calls "time zero" around February, when AI demonstrated legitimate capacity to build models. Initial anxiety about obsolescence quickly gave way to a different realization: professionals need stronger modeling skills than ever.

The shift occurred because AI hasn't replaced the need for human expertise. "At the end of the day, the trust and the confidence comes from a human delivering a message to another human," Schnoor said. Company leadership still demands subject matter experts who understand model mechanics and can vouch for accuracy.

The current challenge is using AI to expedite manual processes while maintaining the insight and knowledge required to inspire confidence in results.

Building the framework

Schnoor, who began his career as an investment banker at Citibank and has led the Toronto-based FMI since 2016, recommends CFOs establish comprehensive AI usage frameworks immediately.

The framework should require transparency on two fronts: how much AI was used in developing a financial model, and what human interaction occurred during the process. "First, tell me how much AI was used, but second, tell me what human interaction did the team do?" he said.

CFOs should also personally experiment with AI tools in early implementation stages, conducting their own checks and stress tests. "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," Schnoor explained.

Preserving human judgment

Maintaining human oversight in decision-making inputs remains critical as AI usage expands. While AI can accelerate manual tasks, "we cannot allow AI to arbitrarily choose inflation rates, interest rates, cost assumptions without having massive insight and oversight into what that means," Schnoor said.

The goal is keeping humans connected to decision-making and inputs while leveraging AI's efficiency gains—a balance that requires deliberate process design and ongoing vigilance.

These details were first reported by CFO Dive.