Should your utility be using AI agents?

Matt Chester (0:00)

Agentic AI, you've heard the term, but what is it really? And how is it already changing the way that energy companies are working? Our guest today on Power Perspectives is AI strategist, Jeff Wilser. And he's here to answer those questions for us. Jeff, welcome to the show today.

Jeff, let's start with the basics. When you say agentic AI workflow, what exactly does that mean? And how is that different than say, someone at a utility company using a chatbot to ask a question? Sure.

Jeff Wilser (0:32)

I know you've had a lot of recent great episodes on AI. So I'm sure many of your listeners have some basics here. But for those who are new to the agent world, I think when most people think of something like ChatGPT or chatbot, it's mostly about just asking a question and getting a response, right? So simple analogy, hey, I want to go to Tokyo for vacation. What do you recommend I do?

An agent would actually do the things for you. So instead of just getting an answer like here is a good itinerary in Tokyo, you can say, hey, I want to buy plane tickets. Please buy me plane tickets, book me hotels. So you can think of it as actually the arms and legs of doing things, not just the brain itself.

Matt Chester (1:19)

Gotcha. That's definitely helpful. It's a little bit more action-based. For our audience that's in the utility and energy world, what's an example of something that maybe one of their employees spends hours doing today that an AI agent could realistically handle?

Jeff Wilser (1:33)

Absolutely. Matt, I think a lot of folks hear about AI agents and they immediately race to the most provocative, scary, crazy thing that can be done.

Some agents who has full autonomy of a control room. But there is a lot of middle grounds and a lot of far less glamorous, more basic things that can be done before you get to that point. I think the number one thing, and this is true of so many industries and top of utilities and energy is paperwork. Virtually every industry, including you guys, we all have more paperwork than we want to do. And that ranging from compliance documents to trying to find what your rates were in some niche area from 12 years ago, there are buckets and buckets of paperwork that no one really has time to do. And AI agents can be built to actually sift through the paperwork and summarize and actually draft documents. So kind of the two year ago and one year ago AI thing was to manually, let's say, feed a PDF into something like ChatGBT or Claude or Copilot and say, hey, summarize this for me.

Now that could be done with far more efficiency where an agent can actually romp through stacks and stacks of paperwork and glean insights and help you create summary documents.

Matt Chester (3:12)

And is the benefit just that it's able to do it that much quicker and more efficiently or do you find that the AI agent can actually do it better too?

Jeff Wilser (3:20)

So in your world, think about a compliance issue that no one analyst could possibly have time to read the hundreds of precedents and documents behind this. But an agent can go through and not just do it faster, but have access to this sprawling amount of paperwork to turn up insights you wouldn't otherwise have known to even look for.

Matt Chester (3:47)

Yeah, that's definitely, I think, something that the utility executives would be eager to learn more about. And you mentioned that people jumped to the idea of like, oh, the AI is running the control room, and then there's a little bit of an aversion to that. But even when you're just looking at the paperwork and the regulatory aspect of it, it's still important. And I'm curious how much you find that there's oversight or fact-checking still needed from the human side of the equation when the AI agents are doing these tasks.

Jeff Wilser (4:14)

For sure. There's a cliché that I'm sure you've heard. But it's one of those clichés that happens to be true, and that's keeping a human in the loop. And that can happen in a couple of different levels, right? You could have the human spot check and look for errors.

Obviously, you want someone to be sanity checking it before it goes anywhere sensitive. But one thing I think that one thing I share when I work with companies and workshops is, yes, human in the loop, but one additional thing you can do to help with control and help guardrails is actually using AI agents and AI models kind of to cross check each other in a bit of adversarial, constructive way, right? So imagine that you, to keep it very simple, imagine you're working with something like Claude to create some agentic workflow and your agent says, aha, I am now going to create this compliance document. You can then feed it to a different system entirely. Let's say in ChatGBT, give it the rules of the road, give it the context and say, hey, I want you with fresh eyes and to get the nice splash cold water here, cold water, I want you to evaluate this and find blind spots. By using AI system to check the other, that can help actually reduce errors and give yourself more of a, again, I wouldn't use the word certainty. A human should always be in a loop, but it's helpful to have AIs check each other and that can reduce errors as well.