The following is a guest post from Jim Caci, CFO of AvePoint. Opinions are the author’s own.
While the CFO role has always been critical for evaluating new investments, the rise of AI in today’s era of cost efficiency has made the CFO a central player in the AI adoption story, with many organizations now leaning heavily on CFOs to evaluate the returns of growing AI investments.
There was a 13% increase in global CFO headcount in 2024, according to consulting firm Russel Reynolds. At the same time, 82% of CFOs have reported an increase in responsibilities in the last year, with roughly a quarter taking on new duties related to IT, digital, and data security or cybersecurity.
As AI adoption continues to spread, with worldwide generative AI spending set to reach $644 billion in 2025, more CFOs will be called on to assess the value of AI-related spending. To do that effectively, they’ll have to focus on justifying and evaluating AI investments, which requires work in areas that extend well beyond the CFO’s traditional purview.
Identify the right use cases for your company and industry
McKinsey’s 2025 Global AI Study found that AI adoption is growing faster than ever, but the way that AI is being used varies greatly by industry and role function.
According to McKinsey, 78% of businesses now use AI in at least one function, up from 72% a year prior. But even as adoption reaches new highs, McKinsey also found that overall usage is highly uneven across different functions and industries.
Thirty seven percent of media and telecom companies say that they use AI in service operation functions, for example, but only 9% of professional services firms say that they use AI in the same area. Similarly, 36% of technology companies now use AI in software engineering, while only 8% of consumer goods and retail companies use AI in that same function.
Additionally, many companies that were using AI in a limited capacity are now expanding their use of AI tools. As a result, CFOs may be called on to help understand where that new investment can have the greatest impact.
The many variables at play in the adoption story mean that CFOs must carefully evaluate their companies’ needs based on original research and industry- and role-specific guidance. Research shows us, for example, that even though AI has become increasingly adept at writing code, it’s still not being used to perform this task evenly across different industries. This highlights the importance of doing your own analysis based on a careful evaluation of your company’s needs.
Past performance does not guarantee future returns, and AI success in one vertical or function may not carry over to another. CFOs must work across the C-suite and collaborate closely with people leaders to assess whether or not there’s a need for AI, and what it is exactly. Ideally, this should involve a detailed pilot program that your team can use to help understand where AI will have the greatest impact and why.
Benchmark and quantify value to justify Investment
While AI is more widely used than ever before, AI tools still require substantial investment, which can lead to greater scrutiny on returns. With AI, this process is complicated not just by the upfront cost, but also by the challenges that some organizations experience when it comes to documenting clear, quantifiable business value generated by the technology.
Gartner recently found, for example, that a third of responsible C-suite officers say that demonstrating the business impact of AI is their top AI-related challenge. While CFOs often share the responsibility for demonstrating the value of new technology investments and driving adoption, they can sometimes be expected to take the leading role when it comes to evaluating the value of AI, given that AI is such a large investment and only 15% of organizations have an AI-related C-suite role.
In that leadership vacuum, the need for CFOs to work collaboratively across departments and workflows to understand the performance of AI technology becomes more important. While day-to-day monitoring likely falls outside of the CFOs direct area of responsibility, they still need to be knowledgeable about these topics and associated challenges so that they can drive change from a higher level.
To quantify productivity gains and progress, for example, companies need to set up robust enablement and support programs to educate their staff on AI best practices and monitor evolving usage.
And even before a company adopts AI, CFOs should work to ensure that their company has established a benchmark for AI progress, either by implementing surveys or by implementing software that can monitor activity on a continuing basis, comparing it against that baseline to show how, where, and when it has added value.
Given the uneven adoption rates between industries, it’s also important to understand how your company’s use and adoption rates stack up against other companies in your industry, since this kind of benchmarking will help you understand where your processes can be most improved. While some of these measures are outside of a CFO’s historical purview, the evolution of the role and the post-zero interest rate policy drive for cost efficiency have made it our business.
Be a strategic advisor, not a budget gatekeeper
As companies increasingly rely on AI, CFOs play a pivotal role in guiding these technological investments. By identifying the right use cases, benchmarking value, and connecting the dots across various departments, CFOs can ensure that AI adoption aligns with strategic goals and delivers measurable outcomes.
Instead of acting as gatekeepers of the budget when it comes to AI adoption, CFOs should also focus on acting as strategic advisors on AI investments. This approach not only enhances the impact of AI but also solidifies the CFO’s influence in shaping the future of corporate strategy.
