Are you ready to revolutionize the utility rate case process with Agentic AI? This session titled “Applying Agentic AI to the Utility Rate Case Process” will showcase how PPL Corporation has created various AI agents to orchestrate faster, more consistent responses to intervenor questions as part of a regulatory rate case. By identifying a business process, quantifying value, and applying a repeatable, agentic framework, PPL has ushered in a new era of efficiency. Agentic AI includes software programs that perceive their environment, understand task intention, and take actions to achieve goals. In this session, we will explore how Agentic AI has been applied to the “Discovery Data Response” process, a crucial part of the rate case process that occurs after a rate case application is submitted to the Utilities Commission and intervenors begin to submit legal requests for discovery. For PPL, the Discovery Data Response process traditionally required over 100 people working full-time or overtime during a 14-day response period. The complexity was compounded by the fact that most of the people involved are not part of the Utility’s regulatory or legal departments as their primary role. They engage only as needed in the formation of a rate case and in discovery response, making collaboration challenging and time-consuming. This utility client identified the Discovery Data Response business process as a prime candidate for AI intervention due to its time-intensive nature and high-value opportunity. The regulatory and legal departments pinpointed this as the most challenging portion of the overall process, where timeliness and accuracy are paramount. Various agents contribute to the overall process, including SME agents, legal agents, an Orchestrator Agent, and Super Agents. The Orchestrator and Super Agents oversee the entire response process, ensuring smooth transitions between agents, avoiding conflicts, and verifying next steps. Key utility roles and personas are mapped to various utility agents, such as Accounting/Finance agents, Regulatory SME agents, Operations agents, Legal agents, and General agents, ensuring appropriate expertise is applied during the response. This agentic approach generates significant time savings and reduces the level of effort and resources involved, specifically reducing the required involvement of non-legal and non-regulatory SMEs. Without agents, initial draft efforts for multiple questions can take days and involve dozens of resources per question. The solution achieves the same outcome in minutes, with agents aware of the entire process, preventing duplicated efforts. Additional value is delivered by reducing the risk of incomplete, inconsistent, conflicting, or incorrect answers. The agents maintain consistent tone, verbiage, and narrative across thousands of answers, eliminating the need for a human editor and significantly reducing errors or conflicts that may harm the case. The approach targets a first-round Data Response but can scale for multiple rounds of discovery. PPL's method can be extended to other utilities, accounting for variations in legal requirements, technical terms, and roles. The agents can be used across the end-to-end rate case process, assembling work papers, preparing applications, predicting intervenor requests, counter discovery, and preparing for hearings. The repeatable structure and agentic tree of the agents are valuable assets. Utilities can learn from the recommended data governance approaches and apply lessons learned throughout the project.