How CFOs Are Turning AI Into a Growth Engine

As AI rapidly reshapes the finance function, CFOs are at the forefront of navigating both the promise and complexity of AI adoption.

In this Q&A with The AI Innovator, Kirstie Tiernan, principal at BDO Digital, shares how finance leaders are shifting their focus from using AI purely for cost-cutting to harnessing it as a strategic engine for growth. She discusses the most impactful use cases, how CFOs can boost AI ROI, best practices for responsible deployment, and why human-AI collaboration will define the future of financial leadership.

The AI Innovator: What AI adoption trends will shape CFO decision-making in 2025 and beyond?   

Kirstie Tiernan: Our research shows that forward-thinking CFOs are moving beyond viewing AI as merely a cost-cutting tool to leveraging it as a growth catalyst. With 60% of CFOs increasing their AI investments, we’re seeing a fundamental shift from reactive to predictive financial management.   

The focus has shifted decisively toward integrating predictive analytics and automated financial processes into core business operations. CFOs are particularly interested in seamlessly incorporating AI into existing enterprise systems, marking a clear transition to more data-driven decision-making.  

Can you cite examples of use cases that are the most prevalent?  

The most successful CFOs strategically deploy AI where it delivers the highest impact. One such area is in leveraging it for real-time financial forecasting, which will become the new standard for F&A departments. AI enables real-time financial forecasting, giving CFOs unprecedented insight into their organization’s financial future.   

What’s particularly impactful about leveraging AI for finance is its ability to uncover insights that were previously invisible to the human eye. For instance, we’ve seen breakthrough results when AI is applied to fraud detection and risk assessment — areas where pattern recognition capabilities are transforming how we protect corporate assets.   

What can CFOs do to improve the ROI of AI?  

The secret to AI success isn’t in the technology itself — it’s in the strategy behind it. Start small, think big, and scale fast. We advise CFOs to take five steps for AI adoption. The first is education — understanding what AI is and what it can and cannot offer for your business.

Step two is identifying the best use cases. This means looking at where AI can target specific pain points in your business. For example, are they having issues meeting compliance deadlines in their F&A department? With managing supply chain inventory? CFOs should first identify the areas of their business where there is a problem to solve. Then, they can explore how AI could address those concerns.  

Once a potential use case is identified, organizations can move to step three — prepare and build. Part of this is being sure they have a strong data foundation before they begin deployment, including developing data governance frameworks, investing in data cleanup, and centralizing data to one single source.   

Step four is to enable and adopt. Successful generative AI adoption cannot happen without employee buy in and training — and 18% of CFOs told us employee adoption and change management is a top challenge for their organization. CFOs have traditionally thought of change management as the last step in the process, but those eager to adopt AI need to consider change management in every step, not just at the end. In 2025, the most successful companies will bring their people along with them on their AI journey through pilot programs, soliciting feedback, and building momentum organically.    

Finally, step five is to go and grow. This means taking the best practices and lessons learned from initial use cases to iterate and scale AI use across your organization. An essential component of implementing any new technology is establishing feedback loops for continuous monitoring and improvement. Leaders should not forget to build this into their process. 

How do CFOs plan to measure the ROI of AI, especially for long-term transformation goals?  

Many CFOs report challenges with justifying investments in AI despite high user satisfaction and significant time savings. An inability to measure and articulate the ROI of AI can leave projects dead in the water, or it can result in difficulty scaling AI across the organization — which 18% of CFOs say remains a key challenge for their companies.   

Traditional ROI metrics don’t tell the full story of AI’s impact. Smart CFOs look beyond immediate cost savings to measure strategic value creation. We recommend developing a balanced scorecard that combines quantitative metrics like cost reduction and output accuracy with qualitative measures such as improved decision-making speed and stakeholder confidence. The key is measuring not just where you are, but how far you’ve come.  

Can you share some best practices for balancing rapid AI adoption with responsible governance?  

Developing a thoughtful, responsible AI policy is a foundational part of the adoption process. Yet despite the importance of responsible AI, only 28% of CFOs say they have formalized or are formalizing a policy.   

Responsible AI adoption isn’t about choosing between speed and governance — it’s about making them work together. Companies adopting AI need to define a plan for using the technology responsibly. This means accounting for bias, drift, and ensuring there is always an element of accountability and human oversight. They should engage a cross-functional team of organizational leadership — and work with an advisor when necessary — to develop their policy.    

What AI regulations are CFOs most worried about? On the flip side, how do they plan to mitigate risks?  

AI is not without risks, but not enough CFOs are thinking about this: Only 41% of CFOs believe their leaders recognize the potential risks associated with AI and are taking steps to address them to improve digital resilience.    

In today’s regulatory environment, the question isn’t whether more AI regulations will come, but when. Even if the U.S. doesn’t introduce any new AI regulations in the short-term, businesses need to be thinking about the future. And for those that operate internationally, some AI regulations, like the AI EU Act, are already here. Smart CFOs are getting ahead of the curve by implementing what we call the ‘trust trinity’ — transparent AI processes, robust risk management frameworks, and regular third-party validations. This proactive approach turns compliance from a burden into a competitive advantage.  

How are CFOs ensuring that AI complements, rather than replaces, human jobs?  

The future of finance isn’t human versus machine — it’s human plus machine. Successful AI implementation hinges on human guidance and expertise.   

The most effective organizations are finding ways to leverage AI for data processing and analysis, while human professionals focus on strategic interpretation and contextual understanding of that data. Rather than replacing workers, AI is elevating their roles to focus on higher-value activities like relationship building, complex problem-solving, and strategic decision-making.   

Organizations are investing in upskilling their teams to work alongside AI systems, recognizing that while AI excels at identifying patterns and processing vast amounts of data, human judgment remains essential for interpreting these insights within broader business contexts.

The future of business isn’t about choosing between human expertise and AI but creating powerful partnerships where each enhances the other. Looking ahead, the most successful business leaders will be those who can effectively bridge the gap between human insight and AI capabilities, fostering cultures that embrace both technological innovation and human creativity.