How AI is transforming financial planning and analysis

In an era of data-driven insights, CEOs can be empowered to drive strategic value and decision-making.

In brief

• Advancements in artificial intelligence are revolutionizing financial planning and analysis and strategic decision-making for chief financial officers.
• Finance leaders can achieve positive returns on investment through areas of AI integration.
• AI can automate manual repetitive tasks and support finance in providing deeper contextual analysis.

In an era where data-driven decision-making and speed are paramount, chief financial officers (CFOs) are turning to artificial intelligence (AI) as a game-changing ally in financial planning and analysis (FP&A). No longer an unachievable concept, AI is now embedded in the very fabric of finance, reshaping how organizations forecast, report and simulate business strategies.

Gone are the days of finance leaders simply reporting on activities and limited by the static data that’s been generated. With the rise of generative AI (GenAI) adoption and agentic AI orchestration, finance teams are empowered to unlock insights at unprecedented speeds, enabling them to focus on what truly matters — driving strategic value and influencing organizational outcomes.

AI is unique in its ability to solve for business forecast accuracy while serving operational bottom-up precision demands. Predictive machine learning improves the accuracy of forecasting, simulates multiple scenarios at differing granularity and generates explainability using natural language models. This further enables the identification of unconventional trends that may have previously gone unnoticed. Combined with agentic AI-supported simulations, finance teams create improved confidence in recommended actions that drive better decision-making.

As highlighted in the report, companies that exemplify successful AI integration showcase the potential for improved financial outcomes. As AI becomes more embedded in FP&A processes, it evolves into a vital component of the decision-making process. Finance teams are now positioned to stress-test business drivers, challenge operational assumptions with evidence, and simulate risk scenarios and optimal resource allocation decisions. This shift is not theoretical but measurable. To remain competitive, FP&A leaders no longer question whether to adopt AI, but how to do it effectively.

Overcoming challenges in AI integration

Despite the promising benefits, challenges remain in integrating AI into FP&A. Cultural resistance and leadership inertia can impede progress, as many finance professionals are accustomed to leaning on traditional and individually managed toolsets like Excel. This resistance is often reinforced by leadership mindsets that favor the status quo or lack a clear vision for integrating AI.

“The true edge in AI isn’t just smarter models — it’s smarter data,” says Aaron Shifrin, EY Americas Business Planning Reporting & Analytics Solution Leader. “Data quality is what powers meaningful intelligence. That’s why finance leaders must play a central role in shaping it.”

Many organizations experiment with AI without a strategic plan, leading to the underutilization of tools. To address this, organizations need strong CFO-level sponsorship and a compelling vision that aligns AI initiatives with business objectives. CFOs should demystify the technology and encourage adoption by educating their teams on AI capabilities and asking them to reimagine processes and new ways of working.

Revolutionizing how finance teams operate

The integration of AI into core FP&A processes signifies not just technological advancement but a fundamental shift in the finance operating model. As AI continues to expand, CFOs and other finance professionals will need to adapt their roles to effectively manage data and AI solutions while ensuring ethical oversight. Developing trust and governing data foundations are critical where CFOs don’t own all of the data elements yet understand how best to connect them.

The challenge is not control — it is orchestration. FP&A needs to operate as the translator across product domain owners, creating a semantic layer to maintain shared definitions for metrics, data contracts and product ontologies. This approach enables cross-collaboration and understanding of shared contexts among different enterprise teams.

Ryan emphasizes, “Transformations are more successful when leaders articulate a compelling vision and align their teams around it.” AI is not about replacing finance teams but rather about augmenting human insight, elevating the teams’ role and impact.

CFOs recognize that AI offers the potential to transform fragmented FP&A processes and business support into a strategic asset. By consolidating finance activities and embedding AI workflows, organizations can cut costs, boost productivity and enhance scalability, ultimately driving enterprise value. Organizations that embrace AI-first transformation will be well positioned to lead the future of finance.