How Connected Nation’s AI models help states monitor BEAD compliance

Washington, D.C. (July 27, 2026) – Did you know that Connected Nation (CN) is utilizing AI and machine learning to assist states in monitoring Broadband Equity, Access, and Deployment (BEAD) projects?

CN’s very own Vice President of Data Strategy & Technical Services, Colin Reilly, recently shared how this risk modeling and sampling approach is designed to identify risks early on instead of waiting until BEAD projects are finished.

Reilly was a special guest on Fiber Broadband Association’s webinar, Fiber for Breakfast. The episode, titled “Intelligent Oversight: How AI is Changing BEAD Compliance,” focused on CN’s framework for monitoring BEAD compliance.

"It's an opportunity to potentially address issues before they become too problematic and they cannot be addressed,” Reilly said.

That’s CN’s framework in a nutshell. It’s a way to identify a project’s risks before it’s too late.

The approach combines data analysis with on-the-ground inspections by experienced technicians. AI models determine which projects and locations should be checked, while technicians visit sites to verify construction progress, equipment, and broadband performance.

But what happens if a project is found to be high risk? 

"We're not saying that just because it's high risk, it means it's going to fail," Reilly said.

High risk means a project needs some additional oversight. CN’s job is to identify those risks early before they escalate into something more serious.

This strategy, known as independent verification, means that instead of solely taking a broadband company's word that it met the requirements of a federally funded project, CN independently checks the work.

"The objective here is just to give the states or territories more confidence and an independent verification that the project was built to the contract specifications," Reilly said.

To learn more about CN’s work with BEAD monitoring, click here.

To watch the full episode and hear more from Reilly, click here or on the below video.