“We will explore how widespread AI use has forced networks to evolve, requiring more capacity and more complex designs so that AI can run efficiently on those networks,” said U.S. Senator Deb Fischer (R-Neb), Chairman of the Senate Commerce Subcommittee on Telecommunications and Media, in her opening statement. “We will consider how government, providers, and other industries are responding to that demand. Private companies have invested hundreds of billions of dollars in network deployment in recent years. Various federal broadband programs have also provided billions to support targeted network deployment and maintenance throughout the country.”
Others who testified came from organizations including U.S. Telecom, Vanderbilt University, and Nebraska Public Service Commission.
“AI is changing not only the volume of network traffic, but the behavior. Cisco measured a fourfold increase in AI inference traffic over eight months. Networks have traditionally been optimized for content flowing downstream. AI is far more two-way and uplink-intensive: prompts, context, sensor data, and agent activity all travel back toward AI models, and the resulting connections are active longer than conventional web transactions,” said Everson. “AI agents amplify these effects by operating at software speed. In our testing, an agent generated 450 percent more traffic than a person performing the same task, and roughly 70 percent of that additional traffic was inference.”
