Something is shifting at the top of the finance function, and it is worth paying attention to if you are anywhere on the path toward those roles. CFOs and controllers are not just adopting AI tools the way an analyst might experiment with ChatGPT for a memo draft. They are starting to rethink how their teams are structured, what they spend their own time on, and what they expect from the people reporting to them. Those changes ripple downward.
What CFOs Are Actually Using AI For Right Now
The most honest picture here is that CFO adoption of AI is uneven. Some are leaning in aggressively, and some are still largely delegating the question to their technology teams. But the ones who are engaging directly are gravitating toward a few specific use cases.
The first is board and investor communication. CFOs who are using generative AI are finding it useful for drafting earnings commentary, board presentation narratives, and investor-facing documents. Not because the AI writes better than they do, but because having a structured first draft to react to is faster than starting from scratch. The thinking is still theirs. The typing is delegated.
The second is scenario analysis and strategic planning support. CFOs are starting to use AI to rapidly model financial scenarios for major decisions, acquisitions, market entries, cost restructurings, so they can arrive at conversations with a broader range of financially modeled options than their teams would have had time to build manually. This is not replacing financial judgment. It is expanding what gets considered before a major decision.
The third, and perhaps most consequential, is workforce and efficiency planning. CFOs are using AI-assisted analysis of their own finance function’s cost and capacity to identify where automation can reduce headcount requirements, and where human expertise is still genuinely necessary. That analysis is directly shaping hiring decisions right now in many organizations.
How Controllers Are Changing Their Day-to-Day
The controller role sits at an interesting intersection. Controllers are responsible for the accuracy and integrity of financial reporting, which means they need to be skeptical custodians of AI outputs rather than enthusiastic adopters who trust the output and move on. At the same time, the tools that are genuinely improving the close process and the quality of financial data are tools controllers need to understand and endorse.
In practice, many controllers are finding AI most useful in three areas. The first is accelerating the month-end and year-end close. Automated reconciliation, AI-assisted journal entry review, and intelligent exception flagging are compressing close timelines in organizations that have implemented them properly. A close that took ten days is moving toward five or six at some firms, not because the work is less rigorous, but because the data-handling bottlenecks are being removed.
The second area is internal controls monitoring. AI can monitor transaction data continuously for patterns that suggest control failures, segregation of duties violations, or potential fraud, far more comprehensively than a periodic review can. That is shifting the controller’s focus from running periodic controls tests to overseeing a continuous monitoring system.
The third area is financial reporting documentation. Generating the technical accounting memos, disclosure drafts, and reconciliation narratives that support the financial statements is documentation-heavy work that AI is starting to assist with meaningfully, under controller review.
The Delegation Shift and What It Means for the Team Below
Here is the dynamic that does not get talked about enough. When CFOs and controllers use AI to accomplish in hours what their teams used to deliver in days, the implicit expectation of the team below shifts. The standard for what the finance function should produce, and how quickly, is rising. That is not always being communicated explicitly. But it is being felt.
Finance professionals who are not keeping up with what AI tools can do risk being perceived as slow or costly relative to what is now possible. That is a quiet but real form of pressure. And in organizations where finance leadership is actively using AI, the people who make themselves useful in the new workflow, by knowing how to work alongside AI outputs and add genuine value to them, are the ones who get noticed.
The new expectation in many finance teams is not that you use AI. It is that you are already using it, and your outputs reflect that.
What Finance Professionals Need to Do Differently Now
The most practical thing you can do if you are in the controller-to-CFO career path is to understand how AI is entering your organization’s finance function and position yourself as someone who helps it work, rather than someone who needs to be worked around.
That means getting curious about the tools your firm is adopting or considering, even if you have not been asked to lead the initiative. It means being willing to use AI in your own work, verify its outputs carefully, and be honest about where it helps and where it falls short. Finance leaders who can speak credibly about the practical limits of AI tools are more valuable to their organizations than those who either oversell or dismiss them.
It also means thinking about the mix of skills that will matter for the CFO and controller roles of five years from now. Technical accounting knowledge remains essential. But the ability to translate financial insight into business language, to work across the organization rather than within a reporting silo, and to lead teams in an environment where AI is doing more of the processing work, those capabilities are moving to the center of what a senior finance leader needs.
For a broader view of how AI is affecting finance teams at every level, the piece on Will AI Replace Data Analysts or Just Change the Work? provides useful context. And the in-depth look at What AI Means for Budget Planners and Forecasting Teams covers the specific planning function in more detail.
Not sure where your finance career actually stands relative to where AI is heading? I built MedscopeHub’s free AI Impact Assessment specifically for this. It gives you a personalized score, shows your exact risk and leverage areas, and builds you a custom action plan in minutes. Take it free at MedscopeHub.com
Frequently Asked Questions
Are CFOs using AI differently from the rest of the finance team?
Yes, in notable ways. CFOs are gravitating toward AI for strategic scenario modeling, investor communication drafting, and workforce efficiency analysis. The rest of the team is more focused on transactional process improvement. Both matter, but the strategic use at the top is what is reshaping expectations throughout the function.
Is the controller role at risk from AI?
Not the role itself, but specific parts of how it has traditionally been performed. Reconciliation, close management, and controls documentation are all areas where AI is compressing workload. The judgment, oversight, and accountability dimensions of the controller role remain firmly human, and if anything are becoming more prominent as the technical burden lightens.
What should a finance professional do to prepare for AI at the CFO and controller level?
Develop fluency with the AI tools entering your finance function, not just awareness of them. Strengthen your business-partnering and communication skills, which are becoming more central to senior finance roles. And build a reputation for good judgment about when to trust AI outputs and when to override them, because that combination is exactly what organizations need at the top of their finance teams.