The CFO is increasingly becoming a decision orchestrator. This means helping the organization connect financial planning, load growth assumptions, capital allocation, operational constraints, regulatory strategy, risk management, and customer affordability into one coherent decision-making system.

According to McKinsey, finance teams are already accelerating their adoption of generative AI. In a survey of 102 CFOs, 44% said they were using gen AI in more than five finance use cases in 2025, compared with only 7% the year before. That shift is important, but technology adoption alone will not transform finance.

In an article from Reuters, citing the U.S. Energy Information Administration, U.S. power consumption is expected to reach record highs in 2026 and 2027, driven by AI data centers and electrification. This is not a small forecasting adjustment. It changes how utilities think about capital planning, grid investment, rate pressure, and long-term financial resilience.

For public power utilities, the equation is even more delicate. According to APPA, public power utilities are facing multiple pressures at the same time: major capital investment needs, aging infrastructure, new generation and transmission requirements, and the need to maintain affordability for their communities.

In a more predictable environment, finance could focus mainly on explaining what happened: budget variances, cost trends, capital execution, and performance against plan. Today, leadership teams need finance to help answer different questions:

What happens if load growth accelerates faster than expected? What if a large data center project is delayed, resized, or canceled? How does a change in capital cost affect future rate pressure? Which investments are most exposed to supply chain constraints? How do we balance reliability, affordability, resilience, and financial health?

These are not only reporting questions. They are decision questions. And decision questions require a different finance operating model.

The CFO is uniquely positioned to make trade-offs visible. Not because finance owns every decision, but because finance can translate operational choices into financial consequences, compare scenarios, quantify risks, and create a common language for leadership teams.

It is not about centralizing every decision in finance. It is about making sure that decisions across the organization are connected, comparable, and grounded in trusted assumptions.

AI can help, but only if it is embedded in real workflows. As EY explains, AI is transforming FP&A by automating routine tasks such as variance analysis, plan model execution, and report preparation, allowing finance teams to focus more on action planning and strategic simulation.

From static annual planning to continuous planning. From isolated spreadsheets to integrated scenarios. From dashboards to decision workflows. From reporting accuracy to decision quality. From data availability to decision-ready data. From AI experiments to AI-enabled finance processes.

The next generation of utility finance will not be defined by more reports. It will be defined by better decision systems.

A dashboard can show what changed. A forecasting model can show what may happen. A scenario planning process can show what choices are available. A governed data foundation can create trust. An AI-enabled workflow can accelerate analysis.

But leadership still needs an integrated finance function capable of turning all of that into action.

That is where the CFO becomes central.

Finance is moving from scorekeeper to orchestrator.

The question for utility leaders is simple: Is your finance function designed to report what happened, or to help the organization decide what to do next?

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