Q&A: IBM’s Monica Proothi on the AI era of finance leadership

As generative AI moves from experimentation to enterprise-wide deployment, the role of the CFO is evolving fast—and so are the expectations.

In this exclusive Q&A with The CFO, Monica Proothi, VP & Senior Partner, Global Finance Transformation Lead at IBM Consulting, shares her front-line perspective on how finance leaders are shifting from stewards of financial performance to architects of digital transformation.

Monica explores the biggest opportunities—and most common pitfalls—facing CFOs as they embed AI into strategic decision-making, FP&A, and day-to-day workflows. From the rise of agentic AI to the importance of ethical governance, Monica offers a practical, grounded take on how finance teams can lead the charge—and why the time to act is now.

AI is transforming the finance function at an unprecedented pace. From your experience, what are the biggest shifts you’ve seen CFOs make in response to AI-driven finance transformation? 

The focus has really shifted from if AI should be part of the business strategy to how can we harness AI for efficiency, growth and ultimately a better experience for customers and users.

As businesses look to AI to deliver heightened business performance, CFOs are increasingly stepping into a strategic role, moving beyond traditional financial responsibilities to really shape and influence the generative AI agenda for their companies.

In fact, CEOs believe that CFOs will make the most crucial decisions over the next three years. Some of the biggest shifts include: 

• Embracing Strategic Leadership: CFOs are taking on more strategic roles, helping guide the company’s AI initiatives and ensuring they align with overall business goals. 
• Increased Focus on Data Governance: They are prioritizing data quality and governance to ensure that AI is being driven by accurate and reliable data.  
• Upskilling for the AI era: CFOs are thinking about how they can upskill their teams at the intersection of technology and domain knowledge to ensure they are well-equipped to leverage AI effectively. 

Many finance leaders are excited about AI but struggle with implementation. What are some common pitfalls CFOs should avoid when integrating AI into their finance operations? 

One of the biggest pitfalls is the lack of collaboration between finance and technology teams. Our recent IBV CFO Study found that less than half—only 47%—of CFOs surveyed said their finance teams are closely involved in developing technology business cases. 

To really make the most of AI, you need strong collaboration across the C-Suite, aligning business strategy with technology advancements. CFOs and CTOs need to work together to bridge the gap between business strategy and technology.

For example, finance and tech leaders can team up right from the start of the planning process to create board presentations that include financial analyses and strategic considerations for tech initiatives.

This is something we’re already seeing leading CFOs doing, with 72% identifying their relationship with the CTO as highly important or critical to their success. 

What are some of the most impactful AI-driven use cases you’ve seen in finance that have led to tangible productivity and efficiency gains? 

One of the most impactful uses of AI in the finance function is for Financial Planning and Analysis (FP&A). AI can streamline the data-heavy FP&A process by analyzing key information on market trends, company performance, competitors, pricing, and operations, and even provide actionable recommendations.  

This is where AI will have the greatest potential to impact strategic finance, providing insights and predictions that empower leaders to make more informed, data-driven decisions. 

Companies are under pressure to justify AI investments. How can CFOs effectively measure and demonstrate the ROI of AI initiatives? 

Finance leaders are increasingly being held accountable for the ROI of AI, and they’re feeling the pressure to show tangible returns. In fact, nearly two-thirds (65%) of finance leaders surveyed said they’re under pressure to accelerate ROI across their technology portfolio.  

CFOs need to strike a balance between achieving short-term AI wins and making longer-term investments that capture the full potential of the technology.

The real power of AI lies beyond just immediate financial returns, but in its ability to drive sustained innovation and efficiency over time. 

To measure success, finance leaders have to look at a variety of factors that indicate long-term growth and adaptability. For example, how are your finance teams using the technology? Is there a culture that encourages employees to leverage data-driven insights? Are finance teams empowered to apply their financial expertise to partner with the business to drive increased value?  

Beyond cost savings, what are some of the strategic benefits AI brings to the finance function that CFOs might overlook? 

Success in the finance function often hinges on how quickly you can turn data into actionable insights, and this is where generative AI delivers the most value. It allows finance leaders to tap into a world of unstructured data.

These insights can help CFOs navigate complex risks, make more confident investment decisions, improve the accuracy of reporting and forecasting, and ultimately create new business value. 

Additionally, CFOs shouldn’t overlook how generative AI can enhance their own the skills and expertise.  Finance leaders are inundated with a laundry list of responsibilities everyday, making it easy to get caught up in tasks and lose sight of the human connection.

Generative AI can automate many of those mundane day-to-day tasks, giving leaders and their teams more time to focus on what truly matters: collaboration and strategic thinking.  

Rather than seeing AI solely as a cost-cutting tool, CFOs should view it as a way to stimulate both efficiency and growth, through repeatable and scalable assets.  

What role does AI governance and ethical AI play in ensuring that AI-driven finance transformations are both effective and compliant? 

Your AI is only as good as your data. Having strong data governance in place helps ensure that the data driving these technologies is accurate, timely, and secure. 

Organizations must treat data governance as a strategic priority and embed it into every stage of AI development. This way, AI systems aren’t just effective—they’re also ethical and transparent.

A comprehensive AI governance strategy should span across people, processes, and technology. For example, organizations can establish AI ethics boards and COEs, iterative training, or establish an AI risk management framework to ensure compliance with existing and upcoming laws.     

How is AI redefining the role of CFOs, particularly when it comes to balancing financial strategy with technological innovation? 

While CFOs have always been responsible for managing financial performance and ensuring ROI, today they must also understand the business value that AI can unlock.

They don’t need to be technology experts, but they do need to understand how to leverage AI tools and ask the right questions to identify the most impactful use cases for their organization. 

As CEOs seek ways to boost productivity and drive growth with AI, CFOs are the strategic transformation partners they need. They’re the ones who can evaluate if AI investments deliver strong ROI and align them with the company’s long-term business objectives and financial priorities. 

As finance teams become more tech-driven, what new skills and competencies should CFOs and their teams be focusing on? 

While functional finance skills will remain essential, CFOs and their teams must also develop new skills to leverage AI effectively and responsibly. It’s crucial for finance teams to get comfortable with these technologies and embrace their full potential, seeing them as a way to augment and enhance their work. 

For example, instead of spending hours in Excel spreadsheets, one might spend some of their time learning prompts or even building AI tools that help derive insights to make decisions faster. 

While unicorn candidates—those who excel in domain finance & accounting plus technology—are rare, companies can build high-performing teams by diversifying skill sets across finance, tech, and data analytics. 

Ultimately, as generative AI becomes more integrated into our work and daily lives, innately human skills like questioning, creativity, and problem-solving will become increasingly essential 

What advice would you give to CFOs who are hesitant to fully embrace AI due to concerns about data integrity, compliance, or workforce displacement? 

AI can feel daunting, especially with the rapid pace of change. It’s easy to wait for the “perfect moment,” but in today’s competitive landscape, delaying AI adoption could mean falling behind. My first piece of advice to CFOs who are hesitant is simple: start. 

AI isn’t about doing more with less; it’s about doing more with what you already have. It’s not a matter of replacing human judgment, but rather enhancing it by integrating AI into daily workflows to enhance decision-making and efficiency. 

The truth is, AI isn’t perfect. But by implementing robust security protocols, establishing clear governance structures, and monitoring and adjusting AI models as needed, CFOs can mitigate the risks that come with incorporating new technology. 

Right now, we’re at a turning point—not just for the finance function, but for business as a whole. CFOs are uniquely positioned to leverage their influence and drive innovation for their organizations. The question now is not if we can afford to embrace AI, but how can we afford not to. 

Looking ahead, what do you see as the next frontier for AI in finance? Are there any emerging technologies that CFOs should start preparing for now? 

Generative AI will continue to disrupt the finance function and its use will become broader and more integrated. There has also been a lot of buzz around agentic AI – and for good reason.

These AI systems can assess situations, gather and process data to problem-solve, autonomously execute tasks and learn from interactions, all with minimal human input.

This marks a new frontier for businesses—for the first time, they can not only automate tasks but also improve outcomes in real-time, going beyond incremental gains to drive real value. 

IBM has been at the forefront of AI innovation. What are some ways IBM Consulting is helping finance leaders navigate and capitalize on AI-driven transformation? 

We’re focused on helping our clients transform their finance operations in a way that leads to productivity gains and growth inside their organizations, and helping them leverage AI to achieve that.  

We’re partnering with them in key areas like FP&A, order-to-cash, and source-to-pay to implement AI to streamline processes and make smarter decisions.

Our goal is to work side by side with our clients to pinpoint the AI use cases that will have the biggest impact on their business, going beyond implementation to really maximize AI’s value and drive ROI across the enterprise.  

We also practice what we preach and are applying AI within our own finance function. One of the main ways we use AI is for forecasting.

Traditionally, this has been a manual and time-consuming process, but by leveraging predictive data analytics, we’ve been able to shift to AI-driven forecasts. This has led to outcomes like being able to implement touchless forecasting with 97% accuracy. 

If you had to predict the finance function in five years, what would be the biggest difference from today? 

We’re already seeing the impact that generative AI is having in the finance function today, and this is just the beginning. Right now, we’re still in the early stages of AI adoption in finance but in five years, we’ll see finance leaders move beyond initial, small-scale use cases and shift focus to high-impact areas like FP&A.  

We’re also going to see the CFO role become increasingly more involved in business strategy. CFOs will work closely alongside CEOs, CIOs, and other business leaders to shape the direction of the company, not just through financial reporting but by actively contributing to their organization’s long-term strategic direction. 

Lastly, the future of finance will be built on “AI stickiness,” embracing AI adoption where it becomes a natural part of our everyday activities. Over the next five years, this blend of human expertise and AI will become second nature. 

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