As finance professionals navigate their organizations through the complexities of balancing growth and profitability, regulatory pressures, evolving markets and intense competition, the introduction of AI and its role in the FP&A world has become a topic of much discussion.
While most finance teams I have spoken to agree that AI has the potential to help them in a significant way, many people still have questions.
As we all experience the integration of AI in mainstream software, what will it mean for FP&A professionals’ jobs?
And most importantly, will AI replace humans in Finance?
Short answer: No.
For many decades, FP&A technologies have helped companies streamline processes and automate tasks, enabling finance professionals to shift their time away from the mundane preparation of data towards more value-added analysis and interpretation of financial results.
The introduction of AI represents the next evolution of FP&A technology and a move towards more strategic contributions to corporate performance management.
It not only continues the effort to automate traditionally less satisfying FP&A work, but now also assists with our analysis and interpretation of results, enhancing the strategic advisory contributions of finance professionals at all levels.
In this blog, I’ll explore what the rise of AI—especially generative AI—will mean for FP&A professionals, and how it will help finance teams gain efficiencies and support better decision making.
When speaking about the rapid growth of generative AI, I frequently hear comparisons between the adoption of AI and the earlier widescale adoption of cloud computing. My findings were quite surprising when I looked deeper into this comparison.
When we evaluate the history of cloud computing and look to the launch of the major cloud platforms, the timeline reveals the following:
A timeline of the adoption of the cloud
When we apply a similar analysis to Generative AI platforms, we find a much shorter timeline:
A timeline of the adoption of generative AI
What occurred with cloud technology over a 5-year span took just under 8 months for generative AI. If there was ever any doubt, AI is moving at a pace faster than anything we’ve ever seen before.
We are seeing the integration of AI into just about every piece of technology we use, and forward-thinking FP&A software vendors have had AI on their roadmaps for quite some time.
In finance, if AI hasn’t already started to help you in your daily activities, I think it’s fair to say that it will be happening any minute.
While AI technology has indeed replaced humans in some settings, my firm belief is that finance will continue to be a human-centric field. It is unlikely, in my opinion, to displace finance professionals in any meaningful way because the core of the field requires:
Complex decision-making: Decisions that are influenced by human judgment, wisdom and ethics, as well as social and emotional intelligence.
Creativity and innovation: Essential for solving complex problems and driving strategic initiatives.
Nuanced communication skills: Critical for effectively conveying insights and strategies and to explain often technical concepts and outcomes to laypersons.
Personalized learning and mentorship: Crucial during the early stages of a career, for developing future leaders and to all on an ongoing basis.
Whether it’s developing and implementing new organizational strategies, identifying creative ways to enhance profitability, engaging with market analysts or developing the next generation of finance leaders, it’s hard to envision AI replacing finance professionals.
Finance professionals aren’t going anywhere. The question to ask regarding the widespread adoption of AI in finance isn’t which people will be replaced but rather, what work will be replaced.
With over two decades of experience working with FP&A technology, I’ve witnessed and been part of some remarkable organizational transformations. I’ve seen cumbersome annual budgets be streamlined from months to weeks, time-consuming quarterly forecasts evolve into on-demand exercises performed multiple times a month and financial consolidations be reduced from several weeks to just a few days.
Earlier generations of FP&A technology have successfully shifted the focus of finance from data preparation to data analysis.
I believe the next quantum leap in finance will come from leveraging AI to augment the analysis capabilities of the FP&A team, with a focus on three key areas:
Natural Language Processing (NLP) is the subset of AI that enables humans to interact conversationally with technology. When combined with generative AI, it can generate complex answers in response to our requests.
FP&A solutions equipped with generative AI capabilities such as Vena Copilot enable CFOs to ask questions in plain language directly to their source of financial truth.
This provides them with real time insights that can eliminate the intermediary step of requesting analyses from their teams to prove their hypotheses. This allows the team to move directly to strategizing and addressing business issues where previously, it may have taken days or weeks to get there.
Pattern and anomaly detection are tools that can highlight data points that may warrant our attention. The patterns can sometimes be quite subtle, and the anomalies often lie deep within our data, making them difficult for the average person to spot.
AI, in contrast can easily navigate large amounts of data to reveal these often-subtle trends and outliers to:
Underline strategies and investments that the organization has already made
Highlight new opportunities deserving organizational focus and investment
Identify errors in budgets and forecasts
At a minimum, the level of validation that anomaly detection can provide will significantly increase the accuracy of forecasts and budgets.
AI predictive modeling employs machine learning and deep learning to predict likely future outcomes. These models look at your current and historical data to determine the trends, relationships, and outliers and then apply new data against these learned patterns to deliver predictions on future results.
The models are further refined through statistical analysis to increase the accuracy of their predictions. This methodology is essential for businesses looking to gain a competitive advantage through data-driven decisions.
Predictive modeling also enables FP&A teams to generate and evaluate a broader range of planning scenarios much more quickly than ever before.
In addition, AI generated scenarios are not burdened with pre-conceived ideas or personal biases and may lead us to evaluate scenarios that we have previously dismissed. Exploring a more complete universe of “what-if” scenarios during the planning process will lead to more optimal plans and strategies for businesses.
We all can agree that AI can produce impressive results, but it’s still important to remember that its intelligence is artificial.
AI can be a source of significant competitive advantage for those who adopt it early and use its power effectively. However, human intuition, experience and judgment remain the most critical components of what finance teams do.
I can say with confidence that AI will continue its integration into the fabric of modern computing and that it will significantly enhance the way finance teams operate.
FP&A professionals should learn how to work alongside AI technologies—both for the benefit of their organizations and for their own personal career development.
For my final word, I don’t see AI having the potential to replace humans in finance, but I do believe that finance professionals with AI experience and skills have the potential to displace those without them.