Complete AI Training
Sign inGet my AI kit

Your job's AI kit

Get your AI kit

Tell us who you are and what you do. We show you your kit right away and email you the link: skills, prompts, AI agents, MCP servers and courses for your job.

500+ jobs ready, and we make a kit for any other job. No payment needed to look.

Share

AI news ·

Why CFOs Trust Generative AI—But Only When It’s Powered by Their Own Data

CFOs trust generative AI most when it uses internal data, boosting accuracy in finance. They’re expanding AI use but keep human judgment central.

2 min read
Management

CFOs Favor Internal Data Over External Sources for Generative AI

Trust is the foundation of finance, and CFOs are proving cautious about where their AI tools get their data. Recent research involving 60 CFOs from U.S. companies with annual revenues above $1 billion shows a growing confidence in generative AI—but only when it relies on internal company data.

Nearly 90% of these financial leaders reported very positive returns from generative AI by the end of last year, a threefold increase since early 2024. Their enthusiasm centers around AI applications in financial modeling, risk management, and forecasting that use their own revenue, cost, and supply chain data.

Why Internal Data Wins CFOs' Trust

CFOs understand that AI’s accuracy depends entirely on the quality of its input. External datasets often contain gaps, biases, or inaccuracies that can lead to misleading results. Instances of AI "hallucinations," where models generate false or misleading information, have only heightened this skepticism.

By contrast, AI tools analyzing a company’s own financial history and operational data provide outputs CFOs can trust. This trust is crucial because any errors in forecasts or risk assessments fall on the CFO’s shoulders in regulatory and shareholder communications.

Generative AI Expands Its Reach

Since early 2024, CFOs have integrated generative AI into an average of four more business areas beyond finance. These include:

  • High-impact areas like cybersecurity management and fraud detection
  • Medium-impact tasks such as customer service automation and content creation
  • Low-impact functions like generating reports and gathering employee feedback

These expanded use cases reflect a pragmatic approach: CFOs are applying AI where it improves efficiency and insights without compromising control.

Measuring ROI and Trust in AI

The survey highlights that 68% of CFOs find generative AI very or extremely important for risk management, with 97% trusting its outputs in this area. For strategic planning and decision support, 76% see AI as highly important, and 98% place significant trust in its results.

Despite the positive results, CFOs remain clear-eyed about AI’s limitations. They view AI as a tool to assist, not replace, human judgment. The responsibility for financial accuracy and compliance remains firmly with them.

Looking Ahead: Increased AI Investment

With tangible benefits now evident, CFOs plan to boost investments in generative AI technologies. The shift from experimental to practical use marks a turning point. However, the principle remains: AI's value depends on reliable data inputs. Garbage in, garbage out still holds true.

For finance leaders interested in building AI capabilities grounded in trustworthy data, exploring targeted education can be valuable. Resources such as AI courses for management professionals help bridge the gap between AI potential and practical application.

Share