CEO Spotlight: SewerAI's Billy Gilmartin on the Future of AI in Wastewater

America's wastewater infrastructure is failing faster than it can be replaced. For years, SewerAI Co-Founder and CEO Billy Gilmartin watched it happen up close. Eager to come up with a solution, he launched SewerAI with fellow Co-Founder Matt Rosenthal in 2019. The California-based company uses AI to upgrade sewer infrastructure inspection and management for all users. The key to modernizing these tasks? Making AI software that is quick enough for engineers, contractors, and operators alike.

You started SewerAI to solve some problems you've noticed in the water/wastewater industry. Which problems were you looking at specifically?

I had built a contracting business that was designed to sell to these large cities in the U.S., focused on cleaning and inspecting their most important sewer assets underground. In building that business, I found that it was really difficult to drive consistency in the quality of the work that we were doing because I had offices on the East Coast and the West Coast. But the other thing I observed was all these utilities were trying to do the same kind of work, yet they were all struggling to standardize the way they do it. I was experiencing two things first-hand: How difficult it was to build and scale a company in this market, and two, the national problem that all these utilities were trying to solve. And I got really frustrated with that. When I met my co-founder, Matthew Rosenthal, who is a technologist, he described this vision of the world that was really compelling. We started this company to completely change the way that businesses operate and how utilities manage our underground infrastructure. If we're ever going to get ahead of the problem, we need to be proactive instead of reactive.

Billy, you come from the business side of things whereas Matthew is more technical. How do you combine your strengths to drive the business forward?

Very early on, Matt asked these really simple and basic questions that were powerful. It was like, "how much inspection do you guys do every year?" And I couldn't answer those questions because I had no idea. So the connection became that he was good at understanding technically how to solve problems while I could connect that to the value of solving the problem and why it matters. Together, we deliver a compelling message to customers because he brings real tangible solutions to the table, whereas I'm helpful in making operators understand what the ROI could be and the difference in productivity could be.

From what we've seen at Water Daily, AI is gradually becoming more accepted by wastewater operators. Have you had the same experience?

I would say people were skeptical of whether or not AI would work or if it could be accurate. So, the first couple of years we spent a ton of time just proving that it could do what we said it would, and how that would help things move faster and provide more accurate information so that they could make better decisions. Now we're seeing the pace of adoption hit a new curve, a new acceleration. I think that's because of a few different things. Number one, the aging workforce in our industry is very real. More than 30% of the entire workforce in utilities is retiring in the next 10 years. As they retire, a lot of the brain trust inside of any utility goes along with them. All the while, they're trying to bring on these younger folks and professionals who expect a different toolset to do their job. I would say the very practical need that any utility has is managing this workforce problem by doing everything with people. This is causing a lot of them to step into the future and adopt technology. What that ends up looking like for us is how fast a utility implements our technology. It's totally different than it was a couple years ago. Back then, it might have taken a year or six months. Now it's taking them only three months. We're benefiting from how rapidly technology is improving, but also that we are building a product that solves a utility's most important challenges.

Where do you think AI has the most potential in the wastewater industry?

In our industry, AI is all about speed of taking action. So to that point, what we've done is create an exponentially faster and more accurate way of understanding where risk is and how to prioritize the things underground that need repairs. Where we'll go next is accelerating how quickly a utility can fix their pipes. If you just look at the news today, one of the main headlines you'll see is that in our nation's capital, Washington, D.C., there was a critical pipe that collapsed right next to the Potomac River. Millions of gallons of sewer started dumping in the Potomac River in our nation's capital. They had the data that would have informed them that that pipe needed to be fixed. There's a lot of work that goes into taking action to fix these problems. People have to design a project, advertise that project, people have to bid on it, then they have to get a contract set up, get a schedule going, and then they actually start doing the work. That whole timeline from knowing you have a problem to actually fixing it could take years. That problem is not unique to Washington, D.C. It's happening all over the country. We've done a really good job at making it really fast and accurate to collect the data and see what projects need to be built. Where we'll go next is helping them build faster so problems like these don't happen again.

A lot of tools in the space are built to serve one type of user. How is SewerAI different in the way it approaches that?

SewerAI was designed to create value for everyone that's working together in the industry. Everything we're building isn't just for a utility, a contractor, or an engineer. It's to help all three of those folks collaborate and perform at a higher level. Our job is to make points of collaboration very high performance and streamlined for the whole industry. That's what the whole company is designed to do.

This interview was edited for clarity and length. Originally published on Water Daily, March 24, 2026.