Latency Kills AI that has the potential to revolutionize entire industries has long passed its demo stage; it now runs through the veins of businesses and will soon become the lifeblood of our economy. From fraud detection and humanoid robotics to autonomous vehicles and real-time language processing, AI is now expected to operate instantly, intuitively and everywhere. But with this shift comes a new bottleneck: latency. No matter how powerful the model or how abundant the compute power, if the network can’t deliver data with single-digit millisecond precision, AI won’t deliver the intended results. The reality is simple – without ultralow-latency connectivity, there is no viable future for AI at scale. That’s why I was pleased to join Tonya Witherspoon of Wichita State University and Hunter Newby of Connected Nation Internet Exchange Points (CNIXP) for a webinar on one of the most overlooked constraints in digital infrastructure: round-trip delay (RTD). While our conversation covered AI, network design and public-private collaboration, the central message was clear: we cannot solve tomorrow’s challenges with yesterday’s networks. Latency isn’t just a technical metric; it’s an economic limiter, a competitive differentiator, and now a make-or-break component of AI. Below are five key discussion points from our webinar, titled “Latency Kills: Solving the bottleneck of RTD to unlock the future of AI,” on why solving the latency challenge – both locally and nationally – is the next critical step on the road to AI mastery. 1. Low latency is no longer optional AI applications are no longer abstract, back-end computations; they are real-time, front-line systems that increasingly underpin daily life. Whether it’s a fintech company performing fraud detection at a keystroke, a vehicle processing sensory data on the move or a manufacturing plant using robotics for precision tasks, latency has become the hard ceiling of performance. As I’ve said many times before, latency is not just a metric – it’s currency. For 4K streaming, the boundary is around 15 milliseconds. For high-frequency trading and autonomous driving, it’s under 5 milliseconds. And when we enter the realm of humanoid robotics and AI agents that interact like humans, we’re talking about single-digit millisecond responsiveness, and that translates to a physical radius of 50 to 150 miles. Beyond that range, the round-trip delay is too high, and the application breaks down. As Newby puts it, “Fraud detection from the major banks is something that they want to do at the keystroke, on the phone, as it’s occurring. That’s a 3 or sub-3 millisecond requirement. Without the right physical infrastructure in place – land, buildings, fiber and an internet exchange – it simply can’t happen. We’re talking about needing thousands of facilities like that across the U.S., and they don’t exist.” This is the kind of performance that enterprises must now design for, and it’s impossible to achieve without rethinking where infrastructure lives and how data moves. Adding more compute capacity won’t solve the problem if By Ivo Ivanov AI & AUTOMATION Five reasons interconnection is the missing link in AI infrastructure 10 CHANNELVISION | SUMMER 2025
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