AI is shifting finance professionals away from routine financial processing and towards roles that demand greater technology fluency, business judgment, and oversight of intelligent systems. As AI takes on more of the work involved in routine accounting operations, finance teams have greater scope to interpret the results and advise on business decisions. The challenge for finance leaders is to equip employees with the skills to direct AI-enabled work while maintaining accountability for its outcomes.
What skills do employers expect from finance professionals in the age of AI?
Technology fluency is becoming an important part of the finance professional’s skill set, alongside the accounting knowledge needed to evaluate financial work. Yet finance teams are still working to develop the skills required. A 2025 survey by AICPA & CIMA found that 56% of finance and accounting leaders and managers identified generative AI as a major skills gap, while half cited shortages of talent and skills as the biggest barrier to adopting new technology.
For Patrick Villanova, chief financial officer at BlackLine, this skills gap highlights the importance of looking beyond traditional qualifications when hiring. He wants to know how candidates have used technology to improve financial processes, whether by automating manual tasks or working with IT to improve departmental systems.
His approach reflects an expectation that finance professionals will take a more active role in improving the processes they rely on. Doing so requires a willingness to explore new technology, supported by enough financial knowledge to assess whether its outputs are correct and suitable for use.
“You’re looking for that mentality, that mindset, that hunger, that zeal to take on and rethink the entire way that they do their jobs and to leverage this technology with open arms, but with prudence and responsibility.”
How AI automation shifts finance from processing data to advising the business
By reducing the time spent processing routine financial transactions, AI could give finance professionals more scope to examine performance and advise colleagues on business decisions.
For example, a team that spends less time compiling a report could devote more attention to understanding why costs have increased and whether the change warrants a response. Its contribution would extend beyond explaining the figures to helping the business assess its options and understand the financial implications of acting on them.
Villanova sees opportunities for employees to influence decisions earlier in their careers as less of their time is devoted to processing data and transactions. He describes colleagues in departments such as sales and marketing seeking finance’s help to interpret the information available to them.
“You had to get to a certain level before you had a sphere of influence and a sphere of leadership and impact,” he says. “That’s happening earlier in people’s careers because other departments are looking to us to help them out.”
Who is accountable when an AI agent does finance work?
AI agents are intelligent systems that can independently carry out tasks and take actions towards a defined goal. In finance, they can perform activities such as reconciliations or preparing journal entries, raising questions about what they should be authorised to do and when human approval is required.
Villanova approaches this from his prior experience as an auditor, where the expectation is that someone can explain why a number is correct and provide the evidence supporting it. Using an agent to perform the work still requires a person who can answer for the result.
“Even if an agent is reviewing the work of another agent, at some point somebody has to own the output of what’s being performed,” he says.
In describing what BlackLine is building, Villanova outlines a process in which an agent completes a defined amount of work before pausing for human review. The reviewer can approve the work or return it for correction, providing a point of control before the agent continues.
Establishing those boundaries requires teams to consider the information an agent can access and the consequences of the actions it can take. They also need a record of the work performed and any approvals, so that a decision can be traced and defended when questioned. Finance’s experience with controls provides a basis for determining how that oversight should operate.
What skills do finance professionals need to work with AI agents?
Finance professionals will need to combine their accounting knowledge with an understanding of how AI produces information and where its limitations may affect the result. “They need to understand debits and credits and how finance works. Otherwise, you don’t know what you’re looking at,” Villanova says.
That foundation allows professionals to recognise when an output contains errors or lacks relevant business context, while applying judgment about whether it is suitable for the decision being considered.
Finance professionals don’t need to become technical specialists, but they should understand how AI systems work well enough to recognise their limitations and communicate their requirements to IT.
Communication and leadership skills also become more relevant as employees take responsibility for work performed by AI and advise colleagues on its use. Explaining why a recommendation needs further examination requires both financial reasoning and the ability to make that reasoning clear to others. Developing this combination takes continued learning, which Villanova says leaders must support through funded training and access to appropriate tools.
What are agentic financial operations?
Agentic financial operations is an approach to managing financial processes in which AI agents execute and coordinate tasks within defined controls and under human oversight. Finance teams can automate parts of complex workflows while retaining accountability for financial outcomes.
How finance teams can coordinate work between employees and AI agents
Coordinating work across employees and AI agents requires finance to determine how their contributions fit within a shared process. An agent might gather information and develop an initial forecast, while employees contribute knowledge of planned business changes that may affect the projections.
Villanova describes a forecasting agent using historical results, sales pipeline information, and economic data to develop a forecast. He proposes comparing the agent’s forecast with those developed by employees through a look-back analysis over successive months and quarters.
Finance professionals would be responsible for examining where the projections differ, challenging assumptions and bringing business context to the discussion. As AI takes on more of the analytical work, their contribution will depend on how effectively they can direct these systems, evaluate their outputs, and determine how the findings should inform business decisions. Accountability for the final recommendation remains with the finance team.
What should finance leaders own next as AI takes on routine work?
As AI assumes more responsibility for financial processes, finance professionals have greater scope to influence business decisions. Their role will involve challenging assumptions and applying financial judgment to decisions across the organisation.
Greater influence also brings greater responsibility. Finance must remain accountable for how intelligent systems operate and the outcomes they produce. Combining financial expertise with sound judgment and effective oversight will be essential.
AI is raising expectations for what finance can deliver. The next generation of finance leaders will be measured by how effectively they direct and govern work carried out by intelligent systems, and how they translate financial intelligence into business impact.
Discover how BlackLine is helping finance teams put AI to work while maintaining control and accountability. Explore BlackLine’s approach to agentic financial operations.
AI is shifting finance professionals away from routine financial processing and towards roles that demand greater technology fluency, business judgment, and oversight of intelligent systems. As AI takes on more of the work involved in routine accounting operations, finance teams have greater scope to interpret the results and advise on business decisions. The challenge for finance leaders is to equip employees with the skills to direct AI-enabled work while maintaining accountability for its outcomes.
What skills do employers expect from finance professionals in the age of AI?
Technology fluency is becoming an important part of the finance professional's skill set, alongside the accounting knowledge needed to evaluate financial work. Yet finance teams are still working to develop the skills required. A 2025 survey by AICPA & CIMA found that 56% of finance and accounting leaders and managers identified generative AI as a major skills gap, while half cited shortages of talent and skills as the biggest barrier to adopting new technology.
