AI is getting plenty of attention in the electric utility world, largely due to the challenges that associated data centers will bring with them. However, the utility industry could stand to benefit from the power-hungry generative AI (GenAI) technology, and a team at Ernst & Young LLP (EY US) is working to demonstrate just that.
EY decided to focus on the rate case filing process for its GenAI solution, arguing that the regulatory task “demands detailed analysis and strategic planning,” and can often take longer than a year to complete – thus, a nice contender for GenAI tech meant to find efficiencies and reduce process times.
EY says it is the first to create and market a “comprehensive tech-led approach” utilizing GenAI for the rate case filing process, which originally stemmed from a discussion between EY US consultants and a client’s chief information officer over whether technology could assist utilities during rate case preparations.
GenAI can sift through “vast amounts of historical rate case data,” EY said, which can allow it to find information relevant to the rate case process. EY notes that each rate case is “not an isolated event, but part of a continuum,” as each new rate case builds upon the knowledge and outcomes of prior cases. Additionally, EY argues that GenAI can help utilities respond to the “barrage” of questions that come with a rate case filing, as many of the questions will be similar to those asked in past rate cases, and GenAI could adapt the utility’s past responses to those same questions.
Finally, EY says GenAI can help predict regulatory outcomes by referencing historical data. This, the company argues, can help utilities fine-tune their strategies after identifying what factors play the most into approval rates.
Making the case for grid modernization can be tricky, especially when it comes to proactive investments.
Rhode Island Public Utilities Commission Abigail Anthony, in an appearance on the Factor This! podcast, said regulators have to assess whether proposed grid modernization investments are: 1) needed, and 2) needed on a particular timeframe. “That is much harder to do than it might sound,” she noted. That’s in large part due to the shifting of risk from utility to regulator (and ratepayer) with pre-approved investments.
“We might not want to invest in something now that will be nearly fully depreciated by the time of need, should the need even materialize,” Anthony said.
Utilities across the country are beginning to embrace AI, but they’re only dipping their toes in at the moment. Even the most innovative utilities, like PG&E, are taking a measured approach to AI, especially for critical operations.
FULL INTERVIEW: AI is here, and utilities are ready to get out of the ‘sandbox’
For PG&E, deploying artificial intelligence is a bit like working in a “sandbox”—a controlled space where new tools can be safely tested, refined, and adjusted to meet the demanding standards of the utility industry. It’s a cautious approach from one of the most innovative utilities in the U.S. While most utilities now recognize that machine learning and AI will bring significant changes to the industry, there remains a hesitancy to unleash the tools beyond back-office tasks and onto power grid operations.
Technology leaders are sprinting to serve seemingly every industry with AI-powered tools. The utility industry is complicated, however, due to its inability to fail forward faster when it comes to safety and reliability, on top of regulatory scrutiny.
