For many roles, the story of AI’s impact is one of efficiency and time savings. But for the CFO, AI is creating a different outcome: more responsibility.

Once measured solely by the accuracy of financial reporting or the strength of internal controls, CFOs are now facing a new set of expectations. As AI lowers many of the barriers to information and analysis, finance leaders suddenly have the tools to understand their businesses more deeply, influence more operational decisions and help drive enterprise-wide performance. Boards increasingly expect the CFO to embrace AI as part of the role. It’s no longer optional. This, in turn, is raising the expectations and broadening the scope for the role of the CFO.

In this GrowthBit, we’ll share four shifts happening within the finance function and look at how finance leaders can approach them to prepare for what’s next.

1. AI is removing data blind spots across the organization

Finance has always needed to monitor the pulse of the business. However, a lack of time, resources and access to data has prevented CFOs from investigating activity outside of finance and developing a deeper understanding of the organization’s long-term financial health. AI is helping to lower some of those barriers.

Consider R&D spending. Understanding what developers are working on, how resources are allocated and what has been deployed can be difficult to unpack without requesting additional information. Connecting AI to a project management system such as Jira can provide a clearer and more immediate view of that activity.

The same opportunity exists in the boardroom. Before AI, a question about a deal in the sales pipeline may have required follow-up with sales leadership after the meeting. Now, sales-call transcriptions and pipeline information can be synthesized with AI, giving finance leaders a way to investigate the activity and provide their valuable perspective.

The information still needs to be reviewed and interpreted, but as the barriers to access lift, CFOs will be expected to understand the operating drivers behind financial performance – not simply report the results they produce. That allows CFOs to ask better questions and become more informed operating partners to the CEO, management team, board and company as a whole.

Companies are testing more tools, considering more use cases and launching more pilots. Each raises familiar finance questions…

2. AI is raising the stakes on the CFO’s traditional responsibilities

For many roles, the story of AI’s impact is one of efficiency and time savings, especially for team members who can eliminate the need to build every report or analysis manually. But for the CFO, AI is creating a different outcome: more responsibility.

CFOs have always played an important role in governance, capital allocation, risk management and operational efficiency. But AI is changing the number and pace of the decisions to which those responsibilities must be applied. Companies are testing more tools, considering more use cases and launching more pilots. Each raises familiar finance questions: What is the business case? What will it cost? What outcome should it produce? How will the organization measure value?

Outside of AI embedded in company product, we see an opportunity for CFOs to help orchestrate AI deployment across the organization – prioritizing opportunities, measuring results and working with technology leaders to understand cost and model tradeoffs. A practical starting point is to inventory manual processes across departments, rank them by effort and impact, and apply the same discipline used for any other investment: build the business case, establish an ROI framework and measure the result.

AI necessitates a pivot from producing the work to reviewing, validating and extracting insights from it.

3. The talent profile inside finance is changing

Traditionally, finance professionals built reports, created analyses and generated different views of the business, but AI is commoditizing these activities. It can now create the first draft of a report, conduct an initial analysis or generate preliminary performance commentary.

Technical finance skills will remain important, and teams still need to understand how an analysis was constructed and recognize when AI output does not make sense. But building formulas, writing queries or producing reports may become less valuable as AI assumes more of the first-pass work. That necessitates a pivot from producing the work to reviewing, validating and extracting insights from it.

The differentiator is knowing what to ask. As AI makes analysis easier to produce, curiosity about the business becomes more important. Finance professionals must identify what should be investigated, ask the questions most likely to uncover something meaningful and apply judgment to the result. Finance teams will continue to need technical fluency, but curiosity and business judgment will become increasingly valuable. Your highest performers tomorrow may not look exactly like your highest performers today.

4. Finance fundamentals are still critical

Expanded access to AI does not reduce the importance of strong data, systems, processes and controls. It amplifies it. Without reliable data, appropriate systems and meaningful KPI frameworks, companies will struggle to deploy AI effectively—and to make wise business decisions more generally.

AI is putting more pressure on organizations to complete that work earlier. Establishing the right foundation within the first 100 to 200 days can better position your company to test AI and agentic workflows. Process documentation is equally important. Structured, repeatable workflows such as reconciliations may be well suited for AI-supported automation. But deploying AI against an undocumented process makes it harder to define the intended outcome, establish controls and determine where human review is required.

Data cleanup and infrastructure have historically been priorities for lower middle market companies, particularly during the first year of an investment. Companies should strengthen their data, systems and processes early so they can test AI use cases sooner, measure their impact and scale what works.

Here’s the bottom line.

AI is changing the role of the CFO and finance teams within the lower middle market. It is expanding the capacity of finance by lowering barriers to understanding the broader business, broadening the CFO’s scope into how AI itself gets deployed, taking on more of the first-pass work required to produce analysis and creating new opportunities to improve workflows. The finance leaders who create the value for their companies in this era will be the ones who use AI to ask better questions, apply stronger judgment and help the organization move faster and invest more intelligently.