AI Is Like Electricity: What That Means for Dental Practices and DSOs

At the DSO Technology Summit in Nashville, I kept hearing variations of the same question: How do we actually use AI inside our organization?

People understood that the technology mattered. What was less clear was where to start, how to connect it to their operations, and what would make it useful to the people running their practices.

I think electricity offers a useful way to understand that opportunity.

In the late 1800s, Thomas Edison backed direct current, while George Westinghouse championed alternating current using Nikola Tesla’s technology. Their competition became known as the War of the Currents. Alternating current gained an advantage because it could transmit power economically over longer distances.

That was a battle over how electricity would be delivered. The larger transformation came from everything people built once they had access to it.

Electricity powered lighting, machinery, refrigeration, and communications. Eventually, it powered computers and the infrastructure that makes AI possible today. Its value kept expanding as people found new ways to use it.

That is the parallel I see with AI in dentistry.

A dental practice might begin by using AI to answer a question about production or identify a scheduling problem. A DSO might use it to compare performance across offices. Those are useful starting points, but they represent only part of the opportunity.

Once AI connects to the right data and becomes part of daily work, it can support a much broader range of decisions.

Think about a large office building. Electricity supplies a common foundation for lighting, air conditioning, elevators, computers, and equipment. Each serves a different purpose, but all depend on the same underlying infrastructure.

Inside a DSO, connected data can provide a similar foundation. Operations, sales, marketing, and leadership need different answers, but their decisions often depend on information from the same practices.

An operations leader wants to know which offices need attention. A sales manager wants to understand where treatment acceptance is falling. A marketing leader wants to connect patient acquisition with business results.

The opportunity is to make that information easier to access, interpret, and act on.

This is where many analytics tools leave too much work to the user. They display the numbers, then expect someone to determine what matters, investigate the problem, and decide what to do next.

A dashboard is valuable, but a practice manager still needs answers: Why did production decline? Are cancellations increasing? Are patients leaving without scheduling recommended treatment? Where should the team focus this week?

AI can help people work through those questions and explore possible explanations. The team still needs to verify the findings and bring its knowledge of the practice to the decision. But the distance between spotting a problem and investigating it can become much shorter.

That is the direction we are taking with Root Data.

We built Root alongside SPG, a 50-practice DSO, and deployed it across its network. Leadership uses it to monitor performance. Sales and operations teams use it to support accountability. Custom integrations help marketing examine patient attribution and how acquisition spending connects to results.

Those departments have different responsibilities. The value comes from giving them a shared view of performance and information relevant to their work.

For another DSO, the priorities may differ. One organization may need better visibility into scheduling. Another may need stronger reporting across its sales process. Another may struggle to connect marketing data with practice outcomes.

The first step is to identify a recurring decision that takes too much time or relies on incomplete information. Connect the necessary data, establish clear definitions, and put the resulting insight into an actual operating process.

Then measure whether it helps.

The employment question deserves the same practical approach. Electricity changed existing work and enabled new industries and occupations. AI will also change tasks and roles, but its effect will depend on how organizations choose to deploy it.

My focus is helping teams spend less time assembling information and more time improving the business: supporting practices, coaching employees, addressing problems, and serving patients.

The electricity analogy is a way to think about possibility. The business case still has to be earned through useful applications.

For DSOs, that starts with one clear problem and a team equipped to act on what it learns. As those applications prove their value, the foundation becomes more useful across the organization.

If you want to explore how Root Data could support your practices or DSO, visit rootdata.ai or contact us to discuss your operational priorities.