Artificial intelligence is not just about algorithms — it's about data readiness. For utilities, implementing AI in finance begins with assembling data from multiple systems, cleansing it for consistency, and formatting it so the AI can "see" relationships across accounting, operations, and engineering. The steps below outline how to prepare your organization's data so that AI models can produce accurate and actionable insights.

As utility finance departments increasingly adopt artificial intelligence tools, establishing a comprehensive AI security policy has become essential. Without clear guidelines, organizations risk exposing sensitive customer data, financial information, and proprietary operational details to potential breaches or unauthorized access.

Artificial intelligence is fundamentally reshaping how finance and accounting functions operate across the utility sector. From automated reconciliations and month-end close processes to predictive analytics and sophisticated rate modeling, AI tools are dramatically reducing manual workloads while delivering improvements in accuracy, analytical depth, and decision-making speed that were unimaginable just a few years ago.

Artificial intelligence is reshaping the workforce at a rapid pace. While AI promises productivity gains and cost savings, it also disrupts many traditional roles—especially in clerical work, customer service, accounting support, data processing, and routine analysis. For organizations and workers alike, the challenge is not whether change will happen, but how to respond thoughtfully and proactively.

Implementing artificial intelligence works just like implementing any new process - you need a plan, training, and the desire to make it effective. This 30-day plan is designed specifically for accountants, controllers, and finance managers at utilities and cooperatives. No coding required. No technical background needed. Just a willingness to try something new—one step at a time.

Artificial intelligence is not a single technology — it’s a process that builds on a foundation of data, systems, and human expertise.

For utilities, implementing AI in finance starts with the data that already exists across billing systems, work management, asset accounting, and ERP platforms.

The goal is not to replace people, but to enhance the precision, speed, and insight of financial operations by automating repetitive tasks and uncovering relationships hidden in large data sets.

Utilities today face a growing demand for transparency, efficiency, and data-driven decision-making. Executives, regulators, and customers alike want to see how the organization is performing financially, operationally, and strategically. One of the most effective ways to meet this demand is by implementing Key Performance Indicator (KPI) dashboards in Microsoft Power BI. These dashboards transform raw data into clear, actionable insights that can be shared across departments and even externally with boards or governing bodies.

There is much discussion about artificial intelligence in various industries and its potential to replace human jobs and positions. Taking a broader perspective, it becomes clear that applications of artificial intelligence in the electric industry are primarily focused on enhanced data utilization for grid management, customer service, system maintenance, and planning.

We continue our journey of exploring uses of generative artificial intelligence in areas throughout the utility - in operations and finance. The AI revolution is transforming the way we look at basic tasks and expanding our horizons when it comes to how the utility business is managed.

Artificial intelligence (AI) tools are increasingly becoming integral to the operations of finance and accounting offices. These tools are revolutionizing how financial data is processed, analyzed, and utilized, leading to significant improvements in efficiency, accuracy, and decision-making.

Embracing AI will make it possible to maximize efficiencies in the accounting and finance departments, open up team members for other tasks, and provide the tools for deeper analysis of customer use of electricity. The depth of AI data analysis will provide additional tools to directly design rates that can modify customer behavior in their electricity use and with choices on how they use electricity.

This article provides a very high-level view of areas used in the accounting and rates functions of power and utilities organizations. The list will undoubtedly grow.