Finance’s Defining Moment

Finance can no longer be defined as the function that closes the books, produces the forecast and reports the numbers. As companies navigate greater complexity with tighter resources, AI gives CFOs an opportunity to recast the role of finance, moving it from explaining performance after the fact to helping drive what happens next. 

According to Tim Garippa, Vice President of Finance Transformation at Workday, that's the distinction many organizations still miss. “A lot of CFOs are minimizing the value of AI by layering it on top of current ways of working.” Garippa says. 

“The businesses getting the most value from the technology are those rethinking how finance operates around it.”

Finance leaders increasingly see AI as the answer to a widening productivity gap. The Hackett Group expects finance workloads to rise by 3.2% this year while budgets and headcount decline by 1.7% and 2.1%  respectively, creating a productivity gap of 5.3% and an efficiency gap of 4.9%.

Yet deploying AI is not the same as transforming how finance works. For many organizations, the first step is embedding AI into existing workflows to automate tasks and improve productivity, but the bigger opportunity is to reimagine those workflows around what the technology now makes possible.

The distinction matters because AI only creates value when it’s embedded in the work it’s meant to improve. If employees still move data manually between disconnected systems, automation may speed up individual tasks while leaving the underlying process unchanged. The question eventually shifts from where AI can fit into today's workflow to how the workflow itself should change when people and AI agents can divide the work differently.

"AI does not rescue a broken process," Garippa says. “If the process remains fragmented, AI accelerates the fragmentation rather than solving it.”

Organizations will naturally be at different points in that journey. Some are identifying individual use cases; others are redesigning processes end-to-end or reconsidering how work should be divided between people and AI. Rather than attempting that transformation across critical finance processes all at once, Garippa advocates a staged approach: to “crawl before you run.”

Workday has created sandbox environments where organizations can experiment with AI-enabled workflows before deploying them into production, Garippa says, allowing new ideas to be tested without disrupting day-to-day operations.

As AI becomes more capable of acting independently, the goal for finance leaders is not to create a fully autonomous finance function. It is to determine which individual activities can operate with greater autonomy, where human oversight remains essential and how that balance should evolve as trust and governance mature.

Hackett's Five Degrees of Agentic Automation gives CFOs a way to think about that progression. In the early stages, AI supports individual tasks while people remain responsible for execution. Over time, activities such as reconciliations, invoice processing, cash application, variance analysis, forecasting and controls monitoring can become increasingly autonomous, potentially evolving into more automated end-to-end processes.

But autonomy is granted one activity at a time, not to the finance function as a whole. The more useful question for CFOs, then, is not simply whether AI can be trusted, but where the human belongs.

Garippa draws a distinction between keeping humans "in the loop" and "on the loop."In highly regulated areas such as compliance, audit and financial controls, close human review remains critical. Lower-risk work, however, can increasingly be handled by AI agents operating under human oversight rather than constant intervention. The challenge is determining the appropriate level of authority for each activity while preserving human judgment, controls and accountability. These decisions are fundamentally changing the mix of skills finance needs. As agents take on more routine execution, the shift is not simply toward fewer roles, but toward different work: more exception management, data interpretation, business partnering, AI oversight and control stewardship.

Tomorrow's accountant is ultimately still an accountant. Core accounting judgment remains essential, but is increasingly paired with data fluency and the ability to explain an AI-supported conclusion to an auditor or audit committee. Garippa expects staff accountants to spend less time on routine processing and more time managing controls and exceptions, while accounts payable and receivable teams move their attention toward supplier and customer relationships and cases that fall outside standard workflows.

For finance leaders, decisions about which activities agents perform, where people provide oversight and which skills those people need increasingly have to be made together. That philosophy also defines Workday's approach to AI. The company looks across value streams such as record-to-report, source-to-pay and order-to-cash, then breaks the work apart to identify where suites of agents can support the roles involved. A unified architecture across finance, HR and operational data gives those agents the context to operate inside business processes with enough control to be trusted.

Artificial intelligence offers finance leaders a chance to do something larger than improve efficiency. If embedded with the right foundations, it can change what the function is known for, moving finance closer to the decisions the business needs to make, rather than leaving it to explain the numbers after the fact.

The CFOs who capture that opportunity will build the conditions for AI to operate inside finance’s most important work. That means trusted data, clear controls and roles redesigned so people keep responsibility for judgment and oversight while agents take on more routine execution. “We are at a point unlike anything we have seen before,” Garippa says.“With the right approach to AI, finance can move from a traditional back-office function into a capability enabler for the enterprise.”

The productivity gap is real, but it is not the point. The point is what closes on the other side of it. Finance organizations that build the right foundation are not just solving an efficiency problem. They are becoming something the function has never been before: the team that drives the decision, not just the one that documents it.