Finance teams, as guardians of an organization’s bottom line and key supporters of business strategy, should be central to every strategic decision. However, they are often brought in late or only play a secondary role in making decisions. Despite this expanding remit and the increased demands, however, finance’s strategic impact has often been limited by fragmented systems, manual processes and delayed access to cross-functional data. That’s finally starting to change.
According to Vena’s 2025 State of Strategic Finance report, 55% of finance leaders who characterize their AI operations as “advanced” or “leading” say they are always involved in business-wide strategic planning — 7% more than average, suggesting that AI is what’s boosting them over the top. However, AI isn’t just supercharging finance within the department: It’s giving finance the chance to finally connect with the entire organization in real time. And businesses that are making this shift are seeing real impacts.
AI’s Acceleration of the Financial Expansion
Financial teams are quickly catching on to AI’s benefits. Vena’s 2025 report found 57% of finance teams now use AI for financial operations. Similarly, a 2024 report from Gartner put the number at 58%, with half of the remaining 42% also planning to adopt AI at some point.
At the same time, finance’s role has expanded beyond budgeting and forecasting. A full 82% of CFOs in an Egon Zehnder survey said their roles had expanded in the past five years. Financial leaders and their teams are now expected to offer insight into company-wide priorities such as cost optimization, workforce planning, revenue strategy, IT investment and adoption and more.
AI has provided these teams the capacity to handle these new cross-functional roles, improving their responsiveness and strategic alignment. Vena’s research found that 51% of surveyed professionals said they “often” collaborate with other departments. If a professional said they had a “leading” AI operation, however, their collaboration frequency jumped to 55%.
With this context, Gartner’s projection that 90% of finance teams will use AI for at least one function by 2026 no longer seems so outlandish.
Connecting Departments by Organizing Data
AI adoption comes with another major benefit for companies as a whole. To function properly, AI-powered tools require clean, structured and well-integrated data. Just feeding a model all the data an organization has likely won’t yield the desired results.
Teams that have employed a data management strategy, meanwhile, have seen the results. Eighty-five percent of respondents told Splunk their strategy “provides sufficient data volume and variety for valuable insights.”
To reap real benefits from their AI investments, they’re being forced to confront long-standing data fragmentation and organizational issues, moving to a data lake model with an emphasis on pulling information from where it’s needed when it’s needed; Deloitte calls this the “octopus in the data lake.”
Better data organization benefits every team, but finance teams who are increasing their cross-collaborational operations particularly appreciate these efforts. Thirty-six percent of finance leaders told Vena that accessing data from multiple source systems was their top challenge.
To put it in perspective, imagine a finance team being asked to rework the organization’s entire global hiring plan in light of current market volatility, but not being able to easily access the HRIS database. With the market situation changing almost daily, the organization would be caught flat-footed and likely end up wasting resources changing the plan repeatedly. Improved systemization enables more accurate planning, continuous forecasting and real-time scenario modeling. In this specific case, AI-enabled data pipelines would be able to unify operational, HR and financial data, enabling finance to lead enterprise-wide decision making with confidence.
Traditionally, finance has been skeptical of AI due to concerns about its accuracy. However, that attitude has also shifted as professionals have seen newer models at work; 82% of finance leaders are now optimistic about AI’s potential impact.
One key reason may be one of the most popular use cases for AI as identified by Gartner: Anomaly and error detection. AI can sift through spreadsheets and catch cascading errors far more efficiently than a person can, a vital benefit when finance teams are being asked to take on more responsibilities. With these tools, teams can rely more on data, reducing the time spent on manual checks and allowing for greater focus and more time spent driving strategic initiatives.
The Next Frontier: Agentic AI and the Intelligent Enterprise
As agentic AI (AI that can take action on behalf of users) evolves, finance will become not just a strategic partner but an operational orchestrator. Agentic systems can proactively take risks (for example, anomalous variances in forecast vs. actuals) and initiate alerts or actions autonomously to the finance team. In another modeled scenario, McKinsey & Company projected that using agentic AI could reduce review cycles by anywhere from 20-60%. These kinds of benefits enable a more proactive, interconnected enterprise. 60%. These kinds of benefits enable a more proactive, interconnected enterprise.
More specifically, AI empowers finance to create enterprise-wide cohesion in several different ways, all of which can be further enhanced by agentic capabilities:
- Guide company-wide investments with real-time scenario modeling.
- Collaborate with HR to align the headcount strategy to the budget.
- Partner with sales and marketing on dynamic revenue planning.
- Integrate with the supply chain team to model operational risk.
It’s critical to note that this isn’t and can’t be just a tech shift. Successfully incorporating AI is a cultural and operational shift, too. Incorporating AI holistically gives every department a shared data pool and the same decision-making language. For finance, this common ground is a solid foundation to build stronger relationships across the organization, breaking down technological and interpersonal silos.
Finance teams that embrace AI are stepping out of the back office once and for all. By cleaning up fragmented data, reducing manual errors and supporting proactive decision –making, AI is positioning finance as the true nexus of the modern enterprise — but just as all data must flow in to finance for the department to make good decisions, data organization (and AI with it) can and must flow out to the rest of the organization, creating a shared operating model — where decisions are faster, alignment is tighter and every team can see the full picture.
