How CFOs can future-proof finance operations with AI

Q&A with Monica Proothi, Global Finance Transformation Lead

With inflation pressures, supply chain disruptions, and regulatory shifts reshaping the business landscape, CFOs are discovering that traditional finance approaches aren't enough. The finance leaders winning today are those who've transformed their operations with AI—not just to survive uncertainty, but to capitalize on it.

We sat down with Monica Proothi, Global Finance Transformation Lead for IBM Consulting who’s helping Fortune 500 CFOs navigate this transformation:

“Finance transformation is no longer a luxury but a necessity in today’s volatile business landscape. CFOs must leverage AI to enhance operational resilience, streamline processes, and drive strategic decision-making. By integrating AI into finance functions, organizations can navigate uncertainties with greater accuracy and agility, ensuring long-term growth and stability.”

Why is operational resilience critical for finance teams today?

Operational resilience is more crucial today than ever before. This is due to changing regulatory requirements, economic uncertainty, increased cyber threats, managing risks, and business continuity. On top of this, the finance organization is still facing the same issues around improving controls and increasing accuracy. In addition, the business environment is fundamentally changing. For finance teams, traditional approaches to planning and risk management are inadequate. You cannot forecast accurately when the rules keep changing. You cannot manage cash flow effectively when payment cycles are unpredictable. Operational risk is not just a compliance issue; it’s a strategic necessity in today’s fast-paced and risk-laden environment.

The key is anticipating disruptions before they hit and being prepared for multiple scenarios. Strong controls, risk management practices, and technology adoption, including automation and AI, are essential to enhance operational resilience. Resilient finance operations safeguard business stability, maintain stakeholder trust, and empower organizations to recover and emerge stronger from disruptions.

How does finance transformation specifically help businesses navigate economic volatility and trade disruptions?

CFOs are constantly striving to master four key areas: control, cost efficiency, accuracy, and growth. They're relentlessly seeking ways to boost productivity and profitability, all while navigating the ever-evolving business landscape and facing headwinds of economic volatility and trade disruptions.

But here’s the exciting part—we’re living in an era where data and technology are not just tools but game-changers.

Let me share what the data shows. Our recent IBV research found that mature AI adopters achieved:

• 25% reduction in planning, budgeting, and forecasting costs

• 33% faster annual budget cycles

• Significantly improved accuracy in financial modeling

These are profound points, but what does this data mean for you? It means enabling your finance teams to leverage AI assistants and agents, and having digital workers frees your team from manual data collection and reconciliation so they can focus on strategic analysis. Imagine streamlining financial processes, making informed decisions with real-time insights, or predicting market trends with unparalleled precision. This isn’t science fiction; it’s the new reality of digital finance. Enhanced financial modeling capabilities allow teams to forecast with increased accuracy and mitigate risks, aiding strategic decision-making. AI can run multiple “what-if” scenarios to assess the impact of regulatory changes and economic fluctuations on margins and cash flow, enabling businesses to anticipate changes and adjust strategies promptly.

What should CFOs know about Agentic AI’s potential in finance operations?

As we know, the technology is still nascent. Agentic AI holds tremendous potential for transforming finance operations. Unlike traditional automation, which only executes predefined tasks, Agentic AI can proactively implement recommendations, reimagining end-to-end processes. Your orchestrated agentic network is made up of single agents, AI agents and large language model (LLM) agents, which create an Agentic AI workforce.

 Think about a Controller who is working on their Forecast. The shift from manual projections to algorithm-defined forecasts using machine learning models significantly enhances the reliability and efficiency of the forecasting process. Integrating a centralized platform that can consolidate data, perform validation checks, and maintain consistent definitions can further streamline operations. Additionally, using AI-enabled variance analysis summaries and GenAI capabilities for explainability supports the Controller in validating and refining the final forecast analysis. The process is more “agentic” by leveraging advanced AI technologies to automate, enhance, and streamline the forecasting process, allowing humans to focus more on higher-level review and decision-making.

What practical steps should CFOs take to implement AI-driven finance transformation initiatives?

To effectively implement AI-driven finance transformation initiatives, CFOs can consider the following four practical steps:

1. Just start. Progress is not perfection. Be curious and embrace experimentation and continuous learning. Use pilots to gain real-world experience, address challenges, and refine your approach. Remember, the journey of a thousand miles begins with a single step, and in the realm of AI, that first step is often the most crucial.

2. Focus on the value areas. Don’t try to “AI” something just for AI’s sake. Create a transformation strategy and map that focuses on areas unique to your business and/or drives business value. The roadmap should align with business needs and have an underlying business case and benefits tracking approach to ensure return on investment, cost reduction, risk mitigation, and insights.

3. Not every data transformation needs to be 100% complete to start. Start with a solid foundation, not perfection. In the realm of data transformation, striving for absolute perfection before initiating your AI journey can be a counterproductive pursuit. It's perfectly acceptable—and often advantageous—to commence with an initial set of cleansed and structured data while concurrently working on refining the rest. Lay a solid foundation by standardizing your organization’s financial and non-financial data definitions. Implement a robust data governance framework, and construct central repositories to amalgamate various data sets, including financial, operational, and external sources.

4. Embrace and champion your Curious Resources; they are the fuel for your engine going forward. The CFOs leading the charge in AI-driven finance transformations understand that technology alone won't drive success. They recognize their teams as their greatest assets and invest in upskilling them. This investment should include data understanding and usage training, foster open communication, and value employee input. 

The bottom line

The finance leaders who will dominate the next decade aren't waiting for perfect AI solutions—they're building competitive advantage with the AI available today. They understand that in a world of constant change, the ability to adapt quickly isn't just an operational necessity; it's a strategic weapon. Adaptability and innovation will be key drivers of long-term success. By proactively embracing AI-driven transformation, finance leaders can ensure their organizations are well-equipped to face future challenges head-on.

To learn more, visit https://www.ibm.com/consulting/finance; download the IBV’s latest agentic AI report on finance, “From AI projects to profits: How agentic AI can sustain financial returns.”