Some of the most useful AI work at RTS happens far away from a customer-facing product. My focus this year has been on something that sounds simple but has enormous implications for any technology-driven company:

Making our data more useful.

The waste industry creates a tremendous amount of operational and financial information. At RTS, that complexity increases as we help customers manage services across large networks of locations. The challenge is not simply collecting more data. It is making sure our teams can understand it quickly enough to make better decisions.

That is where AI has started changing the way I work.

Spend Less Time Preparing the Answer

A significant part of traditional analysis involves preparing information before anyone can actually analyze it.

  • Data has to be organized.
  • Different sources have to be compared.
  • Patterns have to be identified.
  • Inconsistencies have to be investigated.

Our team has been using AI to make portions of that analytical work much more efficient. For me, the breakthrough is not having AI make the decision. It is reducing the amount of repetitive preparation standing between a person and the decision.

When we can do that, our teams have more time to ask the questions that actually matter.

  • What is changing?
  • Why is it changing?
  • Where should we investigate further?
  • What action should the business take?

Improving the Foundation

The work has also reinforced something I believe will become increasingly important as companies race to adopt AI: AI is only as useful as the information underneath it.

Before an organization can build sophisticated intelligence, it needs confidence in how its data is structured and understood. That has been an important part of the work our teams at RTS are doing behind the scenes. We’re creating a stronger foundation so information can move more consistently through the company and the people making decisions can have greater confidence in what they’re seeing.

Customers may never see that work directly. But they experience its impact. Better data supports more accurate execution. It helps teams identify issues sooner. It allows us to make better-informed recommendations. And it creates a foundation on which RTS can build more sophisticated AI capabilities in the future.

Changing the Role of the Analyst

This is also changing how I think about my own job. AI does not make analytical expertise less valuable. It makes it possible to apply that expertise to higher-value problems. If technology can help organize information, recognize patterns or accelerate repetitive work, the analyst can spend more time interpreting what the information means. That is a much more interesting role. And I believe it’s a preview of what is coming across RTS.

The next phase of AI isn’t simply about adding a chatbot to a workflow. It’s about making intelligence part of how the organization operates—giving people better information, faster, so they can make better decisions. A lot of that work will happen quietly behind the scenes. But that doesn’t make it any less innovative. Our customers trust RTS to manage complex waste operations.

The smarter we make the systems behind that work, the better our teams can deliver for them.