The State of AI in FP&A: What’s Working, What’s Next

Executive Summary

Everyone’s talking about AI but what’s really happening inside FP&A teams? Behind all the hype, finance professionals are already experimenting, and automating reimagining how their teams operate.

If you’re a CFO wondering whether your team is ahead of the curve or just keeping up, this report will help you benchmark where you are, spot what’s next, and lead from the front as the rules of finance get rewritten.

AI is everywhere but barely scratching the surface.

79% of FP&A teams are using AI tools but mostly for quick wins. Truly transformative use cases? Still rare.

The excitement is real but action is lagging.

9 in 10 finance professionals say they’re curious or optimistic about AI. Yet 95% spent < 10 hours last month learning how to use it.

It’s saving time but not shaping outcomes (yet).

AI’s current value lies in efficiency. It’s helping teams move faster, isn’t helping them make better decisions.

A new kind of finance team is emerging.

Tomorrow’s FP&A team may include AI analysts & AI systems experts, signaling a shift in finance teams structures.

There’s a governance gap.

Only 28% of organizations have a formal AI usage policy, exposing teams to compliance issues, inconsistent usage, and privacy concerns.

Purpose & Approach

AI has entered the finance function but most teams are still figuring out where it fits. Tools like large language models (LLMs), Microsoft Copilot, and AI-driven financial platforms like Drivetrain are now a part of the finance toolkit.

Much of the current chatter, however, has been anecdotal or about general productivity. There has been little targeted insight into how exactly AI is affecting FP&A.

That’s why we launched this study. Our goal was to uncover what’s actually happening on the ground: how finance teams are using AI today, what they’re concerned about, and where they see the biggest opportunities.

To ground this report in real-world insights, we conducted a survey in July of 2025 and received responses from 258 FP&A professionals.

Trend 01 - Sentiment Shift

Curiosity is turning into action

AI is no longer on the sidelines in FP&A, it’s already at work. Less than 20% have yet to adopt any AI use in their FP&A workflows.

What’s more interesting is the mindset. When asked how they feel about the rise of AI in finance, a large majority of respondents expressed either excitement or curiosity.

Strategic Insight

The mindset shift from AI being viewed as a futuristic concept to something actively being explored signals a pivotal moment for finance leadership. Teams are ready and willing to embrace AI. What they need now is direction.

Opportunity for finance teams

Leverage this openness to drive internal change. Now is the time to roll out AI pilots and upskilling initiatives. Encourage experimentation, document early wins, and scale successful use cases to formal team workflows.

Helping your team see how AI can impact their work and addressing concerns around AI could be one of your biggest leadership levers.

Trend 02 - AI in Action

AI Adoption is real but mostly for tactical use cases.

What’s striking is that these are largely operational, not strategic, use cases. Few teams are using AI to drive scenario modeling, influence planning cycles, or guide cross-functional decisions. In short, AI is helping teams move faster but not necessarily smarter yet.

Strategic Insight

Most adoption today centers on use cases that are easy to implement and show quick returns. This pragmatic approach makes sense given AI’s early maturity in finance. As the technology evolves rapidly, the “moonshots” of today—scenario modeling, dynamic planning, and decision intelligence—are getting closer to reality.

Opportunity for finance teams

To move beyond automation into strategic value, finance teams must first ensure that their data foundations are strong. This means improving instrumentation, cleaning up tracking processes, and giving teams easy access to quality data.

Investing in these areas today not only increases AI readiness but also accelerates your path to higher-impact use cases like forecasting and cross-functional planning.

Some stand-out use cases to take inspiration from

Trend 03 - Tools Behind the Trend

LLMs lead, but specialized tools are emerging.

General LLMs like ChatGPT, Claude, and Google Gemini dominate early experimentation, especially for tasks like generating commentary, writing formulas, or summarizing financial decks. But as teams move toward embedded, secure workflows, enterprise-ready platforms particularly those with native finance capabilities are likely to gain traction.

Strategic Insight

Early AI adoption is being driven by widely accessible tools like LLMs and Microsoft Copilot. But these often operate in silos, disconnected from core financial systems.

Manually stitching data just to prompt an AI model creates friction and limits impact. The real breakthrough will come from finance-native platforms that blend AI with deep financial context, robust controls, and seamless integration.

Opportunity for finance teams

Use these early tools to test and learn, but also evaluate where your AI stack needs to evolve.

Tools like Drivetrain that integrate directly with your financial systems and data infrastructure will ultimately unlock more reliable, scalable automation and insight.

Trend 04 - Where AI Delivers

Speed is the current AI advantage.

Paired with use case data, this shows that the impact is mostly in time intensive but lower leverage activities like commentary generation, spreadsheet cleanup, and deck formatting. Only a handful of respondents are using AI for forecasting or business scenario modeling.

Strategic Insight

While many are experimenting with AI, time savings remain modest, likely due to inconsistent use, limited training, or skepticism. Most teams are still focused on speed and efficiency gains.

As AI capabilities improve rapidly, FP&A teams laying the groundwork by improving data quality, access, and processes will be best positioned to unlock real strategic value.

Opportunity for finance teams

Track where AI is already saving time and use that data to build momentum. Quantify improvements in speed or accuracy to make a case for deeper investment. At the same time, start laying the foundation for high-leverage use cases: get your financial data house in order, streamline access to source systems, and upskill your team to integrate AI into planning and decision-making.

Trend 05 - Skills of the Future

The era of AI demands a new kind of FP&A talent.

It s clear that the most valued skills blend domain expertise with technological fluency and business acumen. Finance teams are no longer expected to simply run the numbers they must explain them, act on them, and increasingly, guide cross functional teams through uncertainty.

Strategic Insight

Finance teams clearly recognize the need to blend technical fluency with communication. However, the time invested in upskilling (refer to Trend 6) suggests they may not be prioritizing this transition yet.

Opportunity for finance teams

Build structured learning into your finance culture. Whether it’s formal training, experimentation time, or peer-led sessions, treat upskilling and AI fluency as a core competency, not a side project.

Trend 06 - Personal Investment in Upskilling

High enthusiasm, low action. The learning  gap is real.

Strategic Insight

While 89% of respondents describe themselves as either excited or curious about AI, this enthusiasm isn’t yet translating into sustained learning effort. Upskilling is happening informally and inconsistently, mostly driven by curiosity rather than mandate.

Opportunity for finance teams

There’s a clear gap between interest and investment. This disconnect signals a moment of opportunity. Finance teams that act now to build internal AI readiness could leap ahead while others are still watching from the sidelines.

Consider creating structured initiatives to help finance professionals build AI fluency. These could include internal AI workshops, monthly “AI challenge” days, team-based prompt engineering contests, or peer-led sharing of use cases and learnings.

How are finance teams upskilling themselves

Experimenting hands-on with AI tools.

Many professionals are teaching themselves. They’re using tools like ChatGPT, Copilot, and various other AI platforms for day-to-day tasks like Excel automation, SQL generation, and report writing.

Following news, newsletters, and social media.

A significant number of finance professionals are staying current by regularly reading finance + AI newsletters, LinkedIn posts, articles, and podcasts.

Improving prompt engineering skills.

Prompting is a common focus, with several respondents practicing and refining how they ask questions or use AI more effectively.

Taking online courses and structured learning.

Some are investing time in formal education via platforms like Coursera, Udemy, and edX, especially around machine learning, Copilot, and prompt engineering.

Peer learning and community engagement.

FP&A professionals are exchanging ideas, best practices, and use cases through peer conversations, workshops, webinars, and networking with technology vendors.

Trend 07 - Re-defining of FP&A Roles

AI isn’t replacing finance teams, it’s reshaping them.

This paints a picture of transformation, not just through tools, but through talent. Tasks once handled by entry-level analysts, data prep, reconciliations, basic modeling are increasingly being absorbed by AI. Meanwhile, demand is growing for finance professionals who can interpret, guide, and influence.

As NVIDIA CEO Jensen Huang puts it: “You re not going to lose your job to an AI, but you re going to lose your job to someone who uses AI."

Strategic Insight

AI is being used most in areas traditionally managed by junior or mid-level analysts (as seen in Trend 2 on top use cases of AI in FP&A). To preserve growth paths, teams must start rethinking how to develop early-career talent in a post-AI environment.

Opportunity for finance teams

Rethink how your team is structured. Shift capacity away from repetitive, tactical work and toward higher-impact responsibilities like business partnering, scenario planning, and strategic advising. Redesign team roles around advisory and business partnership. Define new growth paths for junior staff: AI auditors, prompt engineers, or cross-functional analysts.

What FP&A professionals are saying

Trend 08 - The Role You’ll Need Next

A new wave of FP&A talent is emerging, from outside traditional finance background.

As AI tools become more embedded in day to day workflows, many finance leaders are recognizing a growing need for hybrid roles that blend finance fluency with technical expertise.

Strategic Insight

These aren’t traditional finance roles but they’re becoming mission-critical as data pipelines grow more complex and the use of AI scales across planning, reporting, and forecasting functions. Teams will increasingly need dedicated experts to operationalize AI, bridging the gap between finance, data, and engineering.

Opportunity for finance teams

Start building cross-functional hiring strategies now. Pair financial acumen with technical depth, and build roles at the intersection of finance, data, and AI systems management.

Trend 09 - The Governance Gap

Most finance teams are using AI, few have policies to manage the risks.

Strategic Insight

As AI tools become integral to planning/reporting, the absence of governance policies creates risk. The gap between adoption and policy is wide.

Opportunity for finance teams

Partner with IT and compliance teams to define clear guardrails for AI usage. This is a foundational step for moving beyond experimentation. Focus on four pillars: data privacy, output validation, explainable AI, and human accountability.

Common safeguards finance teams have adopted:

• Avoid the use of real company data in public AI tools and use of anonymized data.
• Restrict use of public AI tools to non-confidential tasks.
• Use enterprise-grade tools with privacy guarantees.

Looking Ahead

AI isn’t replacing finance, it’s redefining it. This report offers a snapshot of AI’s current place in FP&A. And while adoption is growing, the real story is what lies ahead.

Three shifts are already in motion:

From experimentation to integration.

AI use today is still fragmented, applied to spreadsheets, and one-off reports. But the next wave will see AI embedded across the entire FP&A workflow.

From efficiency to enablement.

Time savings are just the beginning. The future lies in AI’s ability to surface trends, generate insights, and elevate the role of FP&A as a strategic partner.

From roles to capabilities.

The traditional FP&A org chart is changing. Instead of replacing people, AI is prompting a re-evaluation of roles and skills. Expect hybrid finance-technical roles, new career paths, and a culture of continuous learning.

The Bottom Line:

AI won’t make FP&A obsolete. But it will change what great FP&A looks like. The leaders who act now, by building skills, setting policies, and testing use cases, will be the ones who shape what comes next.

What Finance Leaders Should Do Next

Treat AI as a team capability, not a personal skill

Upskilling can’t be left to individual initiative. Build learning into your team’s workflow. Run AI playbooks. Bring in outside experts. Make continuous learning cultural, not optional.

Formalize your approach to governance

Get ahead of the curve by defining usage guidelines, data security protocols, and accountability expectations. You don’t need all the answers, just a starting point.

Lead the narrative.

AI adoption will bring uncertainty. Your team will look to you for clarity, confidence, and direction. Don’t wait for top-down mandates. Be the leader who frames AI as the next evolution of strategic finance.

Start hiring for what’s coming.

As data engineers, AI process specialists, and AI analysts become critical to modern finance, start reshaping your team now. Consider rotating finance talent into tech-led projects, or vice versa.

Experiment with real use cases.

If AI hasn’t saved your team time or changed how you work, you’re likely not using it right. Start small. Then scale from there.

About Drivetrain

Reimagining the future of finance with AI at the core.

At Drivetrain, we believe finance isn't just about closing the books or reporting what happened, it’s about illuminating what’s next. And that requires more than faster spreadsheets or smarter dashboards. It requires a new kind of partner.

We’re an AI-native planning platform designed for a new era. One where finance teams act as navigators, not just historians. Where models update themselves. Where reporting writes itself. And where insights come not after the fact, but in the moment they’re needed.

It’s about giving finance the clarity and confidence to lead faster, deeper, and more strategically than ever before.

Because AI won’t replace finance leaders. But finance leaders who use AI will replace those who don’t.