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AI is no longer a futuristic concept; it is a reality transforming how businesses operate. On November 12th,2024, I had the opportunity to host a webinar titled “Data Science Meets Finance: How AI is Redefining Finance & FP&A.” This roundtable discussion featured three experienced finance experts who shared their insights on the current state of FP&A and how AI will impact finance in the future.
The panelists included:
The rest of this article will share thoughts on AI, some of which will come from the great discussion we had with our panelists throughout the webinar.
Even though the level of AI-driven transformation varies by industry and function, the days of speculating if and how AI might impact daily work are behind us. In finance, AI can be used to automate routine tasks, provide real-time insights, and enhance forecasting accuracy. This transformation goes beyond adopting new technology—it reshapes and expands the role of finance and FP&A professionals, enabling them to become strategic partners in their organizations.
In this article, we’ll explore the current state of FP&A, the opportunities and challenges presented by AI, what autonomous finance is, upskilling FP&A professionals, and the practical steps finance professionals can take to shape the future of autonomous finance.
Watch the full webinar here.
FP&A has evolved significantly in recent years. As Kurt Shintaffer noted during the webinar:
“It’s no longer a hot take to say finance needs to play a strategic role.”
Modern FP&A teams recognize that they must act as advisors to business partners, moving beyond the traditional role of “spreadsheet jockeys.”
However, this evolution comes with challenges. Stu West pointed out that the increasing data availability can overwhelm FP&A professionals. The challenge is no longer acquiring data but knowing how to derive actionable insights from it. Many teams experience analysis paralysis—getting lost in a sea of data and struggling with multiple versions of the truth due to inconsistent data sources and definitions. Adding to the sea of data is the challenge of cleaning and preparing data which often takes substantially more time than one would anticipate.
Today’s decision-makers are also more data-savvy and impatient, expecting near-instant insights and the ability to run multiple scenarios on the fly. Questions like, “What happens if we delay hiring by two months?” or “How will a potential revenue dip affect annual targets?” demand immediate answers, not days or weeks of manual modeling.
The good news is that advanced analytics tools and AI-driven platforms are making strides in addressing these challenges. Machine Learning (ML), Robotic Process Automation (RPA), and now Generative AI (GenAI) are becoming integral parts of FP&A and the broader finance organizations. These technologies promise to improve efficiency, accuracy, and strategic value, enabling finance professionals to keep pace with modern business demands. Without improvements in AI and technology moving forward, FP&A will never be able to truly fulfill its mission due to the amount of time spent on low-value tasks such as data cleaning.
One particular area with promise is FP&A Co-pilots, who help provide information and improve our decision-making. Precanto has developed its own FP&A Co-pilot called Ask Precanto to help lead the way in this area.
AI is already making a difference in several key areas of FP&A:
Despite these advances, generative AI’s impact on core FP&A processes remains limited. As the panelists noted, Large Language Models (LLMs) can assist with specific tasks but have yet to fully integrate into FP&A workflows. Finance and FP&A tools, such as Precanto, are beginning to adopt GenAI, but widespread adoption is still in its early stages. Over time we will see more and more adoption of Gen AI as the models improve and companies find more ways to integrate the models within the software we use daily.
AI's Role in Enhancing Decision-Making
AI-driven insights have the potential to transform FP&A operations and enhance the decision-making process by quickly analyzing large data sets and providing insights that would be difficult to find without AI.
However, as Sandeep Madduri emphasized, high-quality data is crucial for effective financial management. AI can process vast amounts of data in real-time, but it cannot compensate for poor data quality. Many organizations must undergo data cleansing before fully leveraging AI’s capabilities. The subject of data quality is brought up regularly by Glenn Hopper, who is a popular AI evangelist and co-host of the popular AI and technology focused podcast Future Finance. He mentions how many companies he comes across want to use AI but can’t due to the quality of their data.
Traditional financial processes often rely on outdated or incomplete information, leading to flawed decisions. Clean data combined with AI offers the promise of real-time analytics, which is more important than ever in today’s fast-paced business environment, where agility and responsiveness are competitive advantages. Enhanced decision-making is one of the primary benefits finance and FP&A professionals seek from AI. When it comes to improving decision-making, every finance professional hopes to see improvement in forecasting and scenario planning, which are often slow and tedious processes in many organizations today.
AI in Forecasting and Scenario Planning
Forecasting and scenario planning are essential FP&A functions. While ML has improved forecasting accuracy, many companies still rely on Excel for these processes. Kurt Shintaffer highlighted AI’s potential to automate scenario planning, making it possible to manage multiple scenarios simultaneously. This capability allows FP&A teams to explore various outcomes and make strategic decisions based on comprehensive analysis.
AI’s role in forecasting is especially promising. Advances in AI will enable forecasts to incorporate diverse data sources, such as sales metrics, economic indicators, and even weather patterns. The result is continuously updated highly accurate predictions.
In addition to improved forecasting, Generative AI (GenAI) and large language models (LLMs) will eventually transform how FP&A interacts with data. Imagine asking, “How would a 5% reduction in Q2 revenue impact our annual profitability, and what hiring adjustments can we make to maintain our EBITDA target?” With the right platform, this question could instantly yield an updated forecast and suggested hiring plan. While we’re not fully there yet, emerging tools push us closer to this vision. Precanto is one of these tools pushing us toward the vision by embracing Generative AI to answer questions about the data we use daily.
The Path to Autonomous Finance
As we advance on this transformative journey of utilizing AI in our daily workflows, one day in the future we look forward to having an Autonomous finance function. Autonomous finance envisions financial insights delivered automatically, without analyst intervention. This doesn’t mean replacing finance professionals; Instead, think of it like a self-driving car for decision-making support: the “vehicle” (your AI platform) takes care of the data navigation, so the business leaders can focus solely on their destination—making better, faster decisions.
In this model, AI proactively detects anomalies, identifies opportunities, and suggests actions. For example, an AI system might alert you to rising supplier costs or ineffective marketing spend, recommending adjustments accordingly.
Achieving autonomous finance will require a combination of robust data management, advanced AI models, and user-friendly interfaces. While full autonomy may still be years away, forward-thinking FP&A teams are already embracing steps in that direction.
Kurt Shintaffer compared finance teams to "manual search engines" for business partners, suggesting that AI could enable self-service capabilities while maintaining the strategic partnership between finance and business units. This evolution requires:
As AI becomes more integral to FP&A, professionals must evolve their skill sets. The panel talked about both technical expertise and strategic business partnering and how some roles might require people to focus primarily on one path or another as we prepare for this AI-driven future.
Regardless of which path someone takes, there will be key skills each of us needs to embrace for the future, some of which are listed below:
· AI Literacy: Understanding the basics of how AI makes predictions and being capable of interpreting its outputs effectively.
· Customer Service Mindset: Maintaining focus on serving business partners and earning a seat at the decision-making table.
· Continuous Learning: Actively experimenting with new technologies and approaches, starting with small-scale implementations.
· Strategic Thinking: Developing the ability to translate data insights into business recommendations.
Every finance and FP&A professional should be finding ways to upskill themselves so they are not left behind as AI starts to play a more prominent role in the daily work we do.
While AI offers numerous benefits, it also presents challenges that need to be addressed. Several of the challenges we need to address are listed below:
AI should augment, not replace, human judgment. Early adoption will likely follow a “human plus AI” model, with AI handling initial analysis and humans providing context and validation.
For FP&A professionals ready to adopt AI, start small and build over time. The process of adopting AI does not need to be daunting. Below are some practical steps to get you started on your AI journey today.
The future of FP&A lies in combining agility, technology, and strategic insight. As Sandeep Madduri noted:
“Finance teams will become more agile and lean, deeply integrated with the most advanced tech out there. Their time will be spent asking the right questions and driving strategic decisions.”
Platforms like Precanto exemplify how AI can empower FP&A, offering real-time insights, scenario planning, and proactive recommendations. With tools like these, FP&A professionals can move from data management to strategic partnership, helping their organizations make better, faster decisions.
The FP&A function has come a long way from being the team that collects data and publishes monthly reports. Now, it has a mandate to help the business make better, faster decisions, whether optimizing spending, rethinking product lines, or exploring new markets. AI provides an unprecedented opportunity to meet that mandate head-on.
AI is in the early days of redefining finance and FP&A, offering opportunities to enhance decision-making, improve efficiency, and drive strategic initiatives. By embracing AI today, finance teams can become more efficient and move closer to embracing the goal of being true strategic partners for the business.
The message is clear: FP&A professionals must actively shape how AI transforms their roles. As Kurt Shintaffer advised:
“Don’t be the resistors. Embrace this change, and it will lead to a more fulfilling career.”
As you explore and embrace AI, remember that success hinges on combining technology, processes, and people. Start small, think like a product manager, cultivate new skills, and proactively communicate value. Over time, you’ll move closer to a future where finance doesn’t just respond to the business—it leads, anticipates, and empowers it.
In that future, FP&A isn’t just about numbers on a spreadsheet; it’s about unlocking strategic advantages. One tool that is already leaning into Generative AI and working hard to shape an AI-data-drive future is Precanto. To learn more about how Precanto can provide you with an AI-Driven Financial Intelligence Platform, click here.
Schedule a demo to learn how Precanto can help your organization.
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