CFOs Give External GenAI Data the Cold Shoulder, at Least for Now

If there’s a cornerstone of the finance function, it’s trust but verify.

In boardrooms across corporate America, finance chiefs are getting comfortable with artificial intelligence, but only when the data is homegrown.

PYMNTS Intelligence’s CAIO Report, encompassing 60 chief financial officers from U.S. firms with annual revenues exceeding $1 billion, revealed a surge in positive ROI perceptions related to generative AI implementations. As of December, nearly 90% of these financial leaders reported a “very positive” ROI from generative AI, a threefold increase since March.

The data showed that CFOs are embracing AI-powered financial modeling, risk management and forecasting tools, but they’re doing it on their own terms and with their own data.

The CFO’s job has always been a balancing act of optimizing cash flow, managing risk and ensuring regulatory compliance while keeping the board, investors and analysts happy. Now, AI tools promise to automate the drudgery and enhance strategic decision making.

However, PYMNTS Intelligence data showed that the AI hype cycle has CFOs walking a fine line. There’s undeniable value in AI-driven financial tools, yet trust is still in short supply.

Finance chiefs are skeptical of AI models trained on external, aggregated data that is often riddled with gaps, biases or outright errors. This skepticism has only grown as AI hallucinations — where AI models generate completely inaccurate or misleading data — make headlines.

Still, the marked increase in ROI is closely linked to the broadened application of generative AI across various business functions. The data showed that CFOs have integrated generative AI into an average of four additional areas since March, encompassing high-impact tasks such as cybersecurity management and fraud detection, medium-impact activities like customer service automation and content generation, and low-impact functions including the creation of summaries and employee feedback.

The successful deployment of generative AI is underpinned by a high degree of trust in its outputs among CFOs.

CFOs are deploying AI tools that analyze their own company’s revenue patterns, cost structures, supply chain data and financial history. AI-driven cash flow modeling, fraud detection and spend analytics are proving invaluable — but only when the CFO knows exactly where the numbers are coming from.

Read also: Since March, Triple the CFOs Report Very Positive ROI From GenAI

The survey indicated that 68% of CFOs consider generative AI to be very or extremely important for risk management, with 97% expressing high or complete trust in its outputs in this domain. Similarly, 76% of CFOs regard generative AI as highly important for strategic planning and decision support, with 98% placing substantial trust in its outputs.

CFOs live in a world of Securities and Exchange Commission filings, Sarbanes-Oxley regulations and audit trails. If AI spits out a bad forecast or misidentifies a financial risk, the CFO, not the algorithm, is the one explaining it to shareholders.

AI models trained on industry-wide or macroeconomic data may inherit biases or flawed assumptions that don’t reflect a company’s unique financial reality. This is particularly true for firms in niche markets or those with atypical business cycles. AI is an assistant, not a replacement. The finance function is embracing AI as a tool to enhance decision making, but not at the expense of human oversight.

Still, the positive ROI and expanded application of generative AI have prompted CFOs to plan for increased investments in this technology particularly as the integration of generative AI into enterprise operations has transitioned from experimental phases to delivering tangible financial benefits.

Ultimately, AI is being pitched as the future of corporate decision making, and CFOs are staking their careers on a longstanding fundamental principle of the finance function: garbage in, garbage out.

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