Artificial intelligence continues to dominate discussion across corporate finance, though many finance leaders are still weighing its practical impact.
Fewer than half (47%) of finance leaders identify AI as the global trend expected to have the greatest impact on their organizations this year, according to Wolters Kluwer’s 2026 Future Ready CFO Report, based on responses from just over 1,600 senior finance executives across 20 global markets.
Recent developments illustrate how quickly AI tools are moving into corporate finance and the risks that come with them. This week’s temporary outage of Anthropic’s Claude model disrupted several finance technology platforms that rely on AI providers’ underlying infrastructure, highlighting how dependent finance workflows are becoming on external systems.
Around the same time, Jack Dorsey’s Block said it would cut more than 4,000 employees while reorganizing teams around AI tools, arguing smaller AI-enabled teams could operate more efficiently.
Those developments reflect only part of the landscape that finance leaders say they are navigating. The survey shows CFOs weighing several forces shaping the business environment. Just under two-fifths (38%) of respondents point to interest rate volatility, while almost an equal amount (37%) identify evolving regulatory complexity as a major influence on their organizations.
The report also describes the modern finance leader as a “performance orchestrator,” a polished way of describing what many CFOs already do, connecting financial insight with data capabilities, technology infrastructure and regulatory requirements across the organization. Market volatility, AI investment and evolving regulations appear throughout the findings as factors shaping how finance leaders approach the future of their roles and organizations alike.
How AI investment spreads across finance operations
AI appears throughout the report as a growing area of experimentation and investment across finance organizations. Forty-three percent of respondents say AI adoption and implementation influence capital allocation and resource planning, indicating organizations are directing funding toward analytics tools, automation platforms and supporting data infrastructure.
Finance leaders surveyed also report expanding use of AI-driven tools across several activities tied to FP&A. Predictive modeling tools, automated reporting systems and performance analytics platforms appear among the technologies cited in the report. These tools are designed to support tasks like forecasting processes and financial scenario modeling by providing faster access to data.
Survey participants also expect AI to influence several core finance activities in the coming years. Financial modeling (63%), financial reporting (62%), capital allocation analysis (62%), budgeting and forecasting processes (62%) and scenario planning (60%) appear among the areas where respondents anticipate notable change within three years.
However, there appears to be room for improvement on the data quality front. Thirty-seven percent of respondents cite data quality challenges among their top concerns around AI adoption, a lower share than those pointing to cost versus return on investment or regulatory risk. The finding suggests some organizations may be making progress on an issue CFOs have long flagged as a required prerequisite for AI adoption.
The forces shaping capital allocation
Several external forces appear consistently in the findings as influences on investment planning. More than a third (37%) of respondents identified regulatory complexity as a factor affecting capital decisions.
Looking ahead, the data suggests finance leaders expect data analytics to play a larger role in investment decisions. Nearly two-thirds (62%) of respondents say AI and advanced analytics will have a major or transformational impact on capital allocation within three years. The expanded use of modeling tools and financial analytics may influence how organizations evaluate investment scenarios and measure performance tied to strategic initiatives.
Developing digital maturity
The report also examined the digital maturity of finance organizations. Most respondents report operating with integrated financial systems and digitized workflows supporting the entire finance function.
Thirteen percent of finance teams classify themselves as digitally basic, while more than two-thirds (69%) report operating in early or established stages of digital maturity, suggesting many organizations have already adopted layers of automation in their core processes.
The most advanced level of maturity remains much less common. Nearly a fifth (18%) of finance organizations identify as digitally advanced, a category surveyors associate with real-time insights, automation and continuous optimization of financial workflows. Many organizations report implementing core systems while continuing to expand analytics and automation capabilities.
Several factors influence the pace of digital transformation. Cultural resistance appears most frequently, cited by just over a quarter (27%) of respondents. Workforce skills also play a role, with nearly a fifth (19%) citing limited digital skills.
Skill development remains a priority as finance organizations modernize. Just over half (51%) of respondents identify data analytics and digital fluency as essential capabilities for finance leadership, alongside AI literacy and cybersecurity awareness, reflecting the growing role of technology and analytics across the finance function.
