Management and technology consultancy BearingPoint has released a new study on the future of the finance function, revealing a widening gap between AI ambition and execution. While CFOs expect artificial intelligence to fundamentally reshape finance, most organizations continue to struggle to move beyond isolated pilots.
CFOs have now a unique opportunity to shape the next generation of the finance function within their organizations
Based on global surveys and in-depth interviews with finance leaders, the study finds that AI is set to reshape forecasting, streamline core finance processes and strengthen decision-making. However, structural barriers continue to limit progress, preventing organizations from scaling AI across end-to-end processes and embedding it into their operating models.
“What our research makes clear is that the barriers to scaling AI in finance are not technological, but rather structural. Data quality, governance, and process design are what determine whether a pilot becomes a scalable capability or stays an experiment. CFOs who treat these as prerequisites, not afterthoughts, are the ones who will pull ahead,” says Olivier Beugnet, Partner at BearingPoint.
AI is reshaping the finance function, but maturity remains low
The finance function is shifting from a reporting role to a strategic partner, with AI accelerating this transformation. CFOs expect more predictive insight, faster decision cycles, and stronger decision support across the business.
However, current maturity remains limited. While 75% of CFOs expect AI to have a high or very high impact by 2030, most organizations remain at an early stage of adoption, with initiatives concentrated in isolated pilots rather than enterprise-wide programs. 73% describe their current AI adoption as minimal or basic, and more than 80% anticipate significant or moderate changes to finance roles within five years.
This gap reflects a broader structural challenge. AI is already demonstrating clear potential in finance areas such as forecasting, automation, and decision support. But without the right data foundations, governance models, and capabilities, organizations struggle to translate this potential into sustained, scalable impact.
Scaling AI remains the central challenge
While many organizations have identified promising AI use cases, scaling them across the finance function remains difficult. Only 9% of CFOs report that AI has been scaled in line with expectations, despite widespread experimentation. Data quality remains the most significant constraint, with 74% of CFOs citing it as a major obstacle to adoption. Fragmented system landscapes, unclear governance, and limited capabilities further slow progress.
As a result, many organizations remain stuck in what the study calls a “pilot trap”. While individual initiatives deliver value, they often remain isolated and fail to translate into enterprise-wide transformation. Without alignment across data, processes, and operating models, scaling AI beyond initial use cases remains a challenge.
Operating model transformation is the unlock
Scaling AI in the finance function requires more than accumulating use cases. It demands a fundamental redesign of the operating model, including processes, data foundations, governance, and roles.
The study shows that leading organizations are already moving beyond experimentation. They are aligning AI initiatives with broader transformation programs, standardizing processes before automation, and building the data and governance structures required for scale.
At the same time, talent and trust are emerging as critical enablers. As AI augments core activities, finance professionals are evolving into analysts who interpret and validate AI-generated outputs. Organizations that invest in hybrid finance and data capabilities, while establishing clear governance and trust frameworks, are better positioned to scale adoption.
This shift marks a transition from isolated pilots to AI as a core capability. Rather than treating AI as a series of projects, leading organizations embed it into systems, processes, and decision-making, enabling continuous performance steering and more predictive, insight-driven finance.
Looking ahead
AI alone will not transform the finance function. The organizations that succeed will be those that redesign how finance operates, not just which tools it uses.
As expectations continue to rise, CFOs face a clear mandate: close the gap between ambition and execution. This requires deliberate action across operating model design, data and system transformation, governance, and workforce development.
“CFOs have now a unique opportunity to shape the next generation of the finance function within their organizations,” comments Kornel Malysch, Partner at BearingPoint. “Those who close the gap between ambition and execution will define how finance creates value in the age of AI, turning insight into action and strategy into measurable impact.”
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