Benchmarking the AI advantage in finance

Artificial intelligence has emerged as a stabilizing force for the finance function. The hype has given way to real-world advancements that let CFOs more easily and accurately plan for future disruption.

To learn how CFOs are using AI to make finance more responsive, unlock real-time insights, and streamline operations, the IBM IBV conducted three separate research studies. We assessed what metrics finance organizations are using to gauge the success of their AI initiatives, how AI-powered processes are moving the needle, and how more mature AI adopters perform on KPIs compared to their peers.

Our research reveals how the most successful finance organizations are tapping AI systems to transform their operations—and where these efforts are delivering the greatest value. We found that mature AI adopters are improving finance performance by optimizing four key processes: financial planning and analysis, order-to-cash, procure-to-pay, and record-to-report.
 

Gaining the flexible finance advantage

As AI-driven transformation redefines growth strategies—and the potential of agentic AI dominates the business news cycle—CFOs are looking for responsible ways to leverage AI’s power in finance.

69% of CFOs say AI is central to their finance transformation strategy—but fewer than 30% are operating or optimizing traditional AI in key processes.

Nearly four in five CFOs plan to maintain or accelerate their finance organization’s pace of transformational change—and 69% say AI is integral to their finance transformation strategy. But successfully implementing AI in finance remains complex. 56% of CFOs cite the execution of AI initiatives as a major obstacle for their finance teams, with 38% saying their finance AI budgets are inadequate to meet their strategic objectives.

Looking forward, CFOs are intentionally prioritizing technology investments to enhance their decision-making capabilities. But AI initiatives often require substantial investments in both technology and talent, which can be a barrier for organizations with limited budgets or expertise.

Additionally, the need for a robust data infrastructure—and the alignment of new AI solutions with existing systems—can slow adoption. Plus, concerns around regulatory compliance, cybersecurity, and the privacy and security of financial data give CFOs pause. They’re also worried about the accuracy and reliability of AI applications, especially in regard to high-stakes financial decision-making processes.

It’s a lot to navigate. As a result, the adoption of both traditional and generative AI in finance remains relatively low. The portion of organizations that are operating or optimizing traditional AI across finance function ranges from 20% to 30%—and that figure is even lower for generative AI.
 

Finance organizations have made limited headway with AI adoption
Percentages reflect respondents who say their organization is “operating” or “optimizing” AI. 

Looking ahead, CFOs are committed to extending the use of AI across finance processes. More than four in five CFOs say it’s important to adopt traditional AI in financial planning and analysis (84%) and procure-to-pay (83%). Similarly, 81% and 78% say it’s important to adopt gen AI in procure-to-pay and order-to-cash, respectively. This widespread intent to broaden AI adoption underscores CFOs’ growing recognition that AI tools can revolutionize finance operations—and that urgent action is needed to stay ahead of the curve.
 

Unlock operational excellence with AI for finance

As organizations are pushed to derive insights from vast amounts of data faster than ever, CFOs are looking to get more of the benefits of AI.

Mature AI adopters complete the annual budget cycle 33% faster and cut annual accounts payable costs per invoice by 25%.

"Mature AI adopters," which we define as organizations operating or optimizing AI technology in their finance function, have been able to reduce costs and redeploy resources at a higher rate than their peers.

This group of leaders, which makes up only 35% of our respondents, attribute a 16% reduction in their total annual finance function cost as a percentage of revenue to AI implementation. This quantifies the substantial gains that come from effective AI strategy execution and underscores the importance of fully optimizing AI's capabilities in finance. These adopters have also redirected 30% of their resources to high-value activities, compared to just 10% for all others.

From forecasting and predictive analytics to improved fraud detection and credit scoring, leading adopters of AI in finance are getting better results from a wide variety of use cases. Read the full report to see how these organizations are using AI to enable the operational efficiency, cost savings, and strategic insights that boost productivity and drive long-term growth.