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AI dominates boardroom agendas, promising everything from decoding the human brain to reshaping how businesses run. Yet for finance leaders, AI too often feels stuck in the trivial, not the transformational. As I wrote in a previous article, the pressure to ‘do something with AI’ is real, but most CFOs are still grappling with a different reality — how to move beyond basic automation and into AI that truly understands the business, delivers strategic insight, and drives collaboration across teams.
The good news is that this gap between hype and reality is starting to close. Finance teams are already using AI in FP&A to improve forecast accuracy, accelerate workflows, and surface insights that drive better decisions. In fact, a recent global survey revealed that 60% of finance leaders say they use AI every day. Yet much of that usage is still happening outside core FP&A activities. Only 52% have adopted AI directly in FP&A, even though those who have are reporting clear benefits such as reduced manual effort, greater transparency, and more time for strategic work.
So why the hesitation? Some CFOs remain cautious about giving AI access to sensitive financial data or worry it could misinterpret accounting rules, regulatory requirements, or even deliver misleading ‘hallucinations’. Others view AI too narrowly as a cost-cutting tool rather than a productivity multiplier that elevates their teams.
This article highlights how AI is already delivering meaningful value in finance workflows, with three high-impact use cases drawn from real finance teams.
1 – From gut feel to AI-powered forecasts
Traditional forecasting can be slow, error-prone, and resource-intensive, often requiring specialized data science skills or endless spreadsheets. AI changes that with intuitive predictive analytics, using machine learning to analyze years of historical data, spot patterns, and forecast outcomes with greater accuracy.
Beyond raw computation, purpose-built AI can add a layer of nuanced comprehension by understanding financial context and natural language queries. It can account for seasonality and trends, reduce bias, and surface meaningful outliers and insights that teams can act on collaboratively.
Rocket Software is a global technology company that helps organizations modernize their IT systems.They use AI-generated forecasts to replace gut feel with data-driven plans, scaling its lean FP&A team while improving accuracy and guiding growth.
Luis Martinez, the company’s Sr. Manager of FP&A said,
We can lean on Planful AI to rationalize our hiring pace by creating upper and lower bounds or pointing out where something looks odd. That helps us have a meaningful dialogue with the business, know where to ask questions, or see where someone accidentally added an extra zero. Best of all, we can do that at scale, without adding finance resources.
Survey data shows the shift is not just anecdotal. 59% of finance leaders report improved forecast accuracy since adopting AI. That aligns with Rocket Software’s experience, where AI can help guide growth with greater precision than gut feel ever could.
2 – Anomaly detection that spots errors at scale
Errors buried in spreadsheets erode confidence and waste hours of analyst time. AI can solve this by scanning massive datasets and surfacing issues in real-time. It works tirelessly and autonomously to signal outliers, potential anomalies, and broken formulas so you can dig into the numbers with confidence. The result? Stronger trust in financial data and more time for analysis and collaboration.
Aurorium, a global specialty chemicals company, leaned on AI to detect anomalies across 89% of its GL combinations, dramatically improving accuracy and relieving FP&A of tedious error-hunting.
The company’s Senior Reporting & Systems Analyst, Robert Franz said,
We inherently trust the data in Planful and don’t question it. Planful allowed us to build our financial processes around data integrity.
Confidence in data is a universal challenge, and AI is making a measurable difference.52% of finance leaders say they have gained increased data transparency through AI. Aurorium’s success mirrors this trend, with AI surfacing errors at scale and giving its FP&A team more trust in the numbers.
3 — Natural language insights that unlock comprehension
Financial data is uniquely complex and full of irregularities — from seasonality and quarterly swings to acquisitions, divestitures, roll-ups, and adjustments. Off-the-shelf AI often struggles to interpret this nuance and can even introduce security risks when handling sensitive financial information (as Planful CTO Sanjay Vyas explains in AI Labs).
With generative AI’s comprehension capabilities, finance teams can start to ask complex questions in plain language — such as ‘what was my consulting spend for January in North America?’ — and receive contextual answers in seconds. Instead of tying up analysts for hours, AI can begin to provide instant insights, highlight related trends, and free teams to focus on more strategic work.
Kimball Midwest is a large industrial supplier that serves thousands of customers across the U.S. So it might be surprising to learn that the business is supported by an FP&A team of just three people. Simple but repetitive tasks, such as running ad hoc financial reports and analysis, can consume time the small-but-mighty team simply doesn’t have.
Kevin Washek, Director of FP&A at Kimball Midwest said,
As the business grows, more is being asked of our team. We’re excited about how AI and technology can supplement our work so we can stay efficient and continue being a valuable resource across the organization.
The efficiency gains are equally striking.57% of leaders report that AI has freed more time for strategic work. That is exactly what Kimball Midwest’s lean FP&A team is seeking, using natural language insights to spend less time chasing ad hoc reports and more time driving strategic decisions.
AI is already adding value for Finance, so what are you waiting for?
AI is no longer on the horizon for finance. It is here, and it is delivering measurable impact. Finance teams are using it to produce more accurate forecasts, detect anomalies at scale, and ultimately to answer complex questions in seconds. The result is greater accuracy, speed, and confidence, with more time to partner with the business on strategic goals.
The opportunity now is to move from experimentation to execution. CFOs who put AI to work in their performance management processes will not only increase accuracy and efficiency, but also elevate finance as a true strategic partner to the business.
Once you see the real value AI brings to FP&A, you’ll wonder how you ever lived without it.
