The Consult

When HRP opened its doors in 1982, the tools of the trade looked a little different. Dan Titus, now HRP’s CEO, remembers those early days fondly—though he “doesn’t like to admit” just how clearly he remembers them.

“We were in an old bank building, and there were two people and one computer per office,” he says. “If you were going to write a report, you had to schedule time with your office mate. In the late ’90s, lots of people still wrote reports by hand and passed them off to a word-processing pool.”

Fast-forward a few decades and every employee has a laptop, work can happen anywhere, and the idea of a report written in longhand sounds like something from a museum exhibit. Each technological leap has increased productivity and protected employees’ time. Now HRP is exploring the next logical tool in that long evolution: AI—specifically Large Language Models (LLMs).

“There’s a lot of resistance to AI everywhere, and certainly we’ve seen some of that internally,” Dan says.

The concern is understandable. People hear “AI” and think “job replacement,” or worry about the environmental cost that comes along with training these models. But the reality at HRP looks a little different.

“At the end of the day, we sell hours. The final work product is delivered in a report,” Dan says. “These reports are often incredibly data-intensive. Lab data alone can be a thousand pages. Historically, someone would go through it line by line.”

The bottom line? AI isn’t replacing the expert; It just speeds up the parts of the work that no one is nostalgic for. Dan sees AI as a tool, nothing more magical or ominous than a wrench.

“In the same way that getting everyone their own desktop, and then their own laptop, and the evolution of different types of field measurement tools going from analog to digital dramatically increased our efficiency, AI has that same potential,” he says.

A focus at HRP has always been an employee’s work / life balance—trying to maintain and respect people’s free time. Adding tools that can make people more efficient supports that goal.

“If AI can help with some of the public-information part of developing a report or some data analysis, you’re cutting into the time required, and protecting that free time.”

HRP’s goal isn’t replacing people. “I think of it like this: AI isn’t building a house,” Dan says. “It might help with the architectural plans, but it’s not swinging the hammer. Someone still has to go out and see what’s happening on a site. I think that’s true in our industry as well. There’s a visual, hands-on aspect of what we do.”

There’s also the question of environmental ethics, a concern Dan acknowledges. AI requires energy. A lot of it.

“I tell people in the company all the time that what we do matters. We protect human health and the environment. While it’s true that there’s a power demand associated with AI, if it can help us do our work more quickly and efficiently, I believe it helps offset some of the more energy intensive aspects. If we can use these tools to accelerate our work and make a real difference in the places we serve, the benefit can have the ability to outweigh the impact.”

AI will not define HRP’s future, but the thoughtful, practical use of it will help shape it. Just as past technologies expanded what employees could accomplish, this next tool can help HRP continue its mission to move the environment forward with care, responsibility and a focus on people.