Leveraging Artificial Intelligence in Utility Finance and Accounting

Abstract

President Trump in his long-awaited AI Action Plan stated [7], “The United States is in a race to achieve global dominance in artificial intelligence (AI). Whoever has the largest AI ecosystem will set global AI standards and reap broad economic and military benefits… Just like we won the space race, it is imperative that the United States and its allies win this race.”
Artificial Intelligence (AI) adoption across U.S. regulated utilities has accelerated in recent years [3][4], particularly in forecasting, asset planning, financial analytics, and self-service capabilities through agents and chatbots. Yet despite growing analytical and execution sophistication, many utilities have struggled to translate AI-driven insights into durable financial decisions, accounting outcomes, or favorable regulatory treatment.
This paper argues that the primary constraint on AI’s impact is not data or model maturity, but the absence of process transformation prior to AI deployment. In regulated utility environments where prudence standards, accountability, and cost recovery mechanisms dominate AI must be embedded within redesigned finance and accounting processes to create measurable enterprise value. AI does not transform utility finance by being smarter; it transforms utility finance by being embedded into smarter processes.
To achieve President Trump’s vision for AI, it is imperative that the Power & Utilities industry move beyond isolated AI use cases and instead adopt an integrated operating model that connects operational execution, financial outcomes, and regulatory recovery. This requires re-architecting the capital and operating lifecycle from planning and work execution to accounting treatment and rate recovery so that AI-enabled insights are systematically translated into defensible decisions, auditable outcomes, and regulator-aligned value realization.
Utilities that succeed will not be those that deploy the most AI models, but those that redesign their processes, governance, and data architectures to operationalize AI at scale elevating finance from a transactional function to a strategic partner in capital allocation, performance management, and regulatory strategy.