The following is a guest post by AvePoint CFO Jim Caci. The views expressed are solely those of the author.

Although CFOs have always played a key role in evaluating new investments, in today's cost-conscious era, the rise of AI has made CFOs central players in the AI adoption process. Many organizations now rely heavily on CFOs to evaluate the returns on growing AI investments.

According to consulting firm Russell Reynolds, the number of CFOs globally grew by 13% in 2024. Meanwhile, 82% of CFOs reported an increase in responsibilities over the past year, with about a quarter taking on new duties related to IT, digital, data security, or cybersecurity.

As AI adoption continues to expand—global generative AI spending is projected to reach $644 billion in 2025—more and more CFOs will be called upon to evaluate the value of AI-related expenditures. To do this effectively, they must focus on justifying and evaluating AI investments, which requires working in areas far beyond the traditional scope of the CFO role.

Identifying the right use cases for the company and industry

McKinsey's 2025 global AI research shows that AI adoption is faster than ever, but how AI is used varies by industry and function. According to McKinsey, 78% of businesses now use AI in at least one function, up from 72% a year earlier. But even with adoption at record highs, McKinsey also found that overall usage is highly uneven across functions and industries.

For example, 37% of media and telecom companies say they use AI in service operations functions, but only 9% of professional services firms report using AI in the same area. Similarly, 36% of tech companies now use AI in software engineering, while only 8% of consumer goods and retail companies use AI in the same function.

Additionally, many companies that previously had limited AI use are expanding their use of AI tools. As a result, CFOs may be asked to help understand where new investments can have the greatest impact. The many variables in adoption stories mean CFOs must carefully assess company needs based on original research and industry- and function-specific guidance. Research shows that although AI is increasingly proficient at writing code, different industries use it unevenly for this task. This highlights the importance of conducting one's own analysis based on a careful assessment of company needs.

Past performance does not guarantee future returns, and AI success in one vertical or function may not be replicable in another. CFOs must collaborate across the C-suite, working closely with HR leaders to assess whether there is an AI need and what that need specifically is. Ideally, this should involve detailed pilot projects that help teams understand where AI will have the greatest impact and why.

Benchmarking and quantifying value to justify investments

Although AI is more widely used than ever, AI tools still require significant investment, which can lead to stricter scrutiny of returns. For AI, this process is complicated not only by upfront costs but also by the challenges some organizations face in documenting clear, quantifiable business value from the technology.

For example, Gartner recently found that one-third of C-suite leaders say proving AI's business impact is their top AI-related challenge. Although CFOs typically share responsibility for justifying the value of new technology investments and driving adoption, given that AI is a significant investment and only 15% of organizations have an AI-related C-suite role, CFOs may sometimes be expected to take a leading role in evaluating AI value.

In this leadership vacuum, it becomes even more important for CFOs to collaborate across departments and workflows to understand how AI technology is performing. While day-to-day monitoring may not be within the CFO's direct purview, they still need to understand these topics and related challenges in order to drive change from a higher level.

For example, to quantify productivity gains and progress, companies need to establish robust enablement and support programs that educate employees on AI best practices and monitor evolving usage. Even before the company adopts AI, CFOs should strive to ensure the company has established an AI progress baseline, which can be done by implementing surveys or software to continuously monitor activity and compare it against the baseline to show where, when, and how AI adds value.

Given uneven adoption rates across industries, it is also important to understand how the company's usage and adoption rates compare to other companies in the same industry, as this benchmarking helps identify where processes most need improvement. While some of these measures go beyond the CFO's historical scope, the evolution of the role and the pursuit of cost efficiency in the post-zero-interest-rate-policy era have made them part of our responsibilities.

Becoming a strategic advisor, not a budget gatekeeper

As companies increasingly rely on AI, CFOs play a key role in guiding these technology investments. By identifying the right use cases, benchmarking value, and connecting the dots across departments, CFOs can ensure AI adoption aligns with strategic goals and delivers measurable results. In AI adoption, CFOs should not merely act as budget gatekeepers but should focus on becoming strategic advisors for AI investments. This approach not only enhances AI's impact but also strengthens the CFO's influence in shaping the future of corporate strategy.