Ever since the advent of voice over IP, responsibility for communications technology has brought with it a vital concern for, if not actual ownership of, the underlying enterprise network. In the world of real-time communications traffic, i.e., voice and video, this has meant understanding Quality of Service (QoS) for IP networks, as well as engineering bandwidth for the often bursty, unpredictable nature of real-time loads. Turns out, this complex task may wind up looking easy next to the challenges AI will present in the next generation of IP networking.
In testimony before the U.S. Senate Commerce, Science, and Transportation Committee’s Subcommittee on Telecommunications and Media, Bob Everson, Cisco’s Chief Architect, Provider Mobility described the impact he’s seeing. An opening caveat: As veterans of the VOIP transition will remember, trends that overload and complicate IP network traffic and performance tend to be very good for Cisco’s stock price, which has basically doubled over the last 52 weeks with the advance of AI. That said, there’s little reason to doubt the findings Everson presented in Washington late last month. Among these:
- Overall, Cisco anticipates a, “209% increase in campus and branch traffic volume in the next three years.”
- AI agents were found to generate, “up to 450% more traffic per task than humans in a Cisco-controlled test.” The impact is already being seen: “Customers report a 34% increase in traffic tied to AI workloads over the last 12 months, and they expect to see a 96% increase this coming year,” Everson testified.
- “Half of enterprise customers report that AI demand is concentrated on their Wi-Fi networks, and 73% of organizations already face or expect to face campus and branch capacity limitations within the next 24 months,” Everson said. If you haven’t been exploring Wi-Fi 7, you’re probably due to start.
- Moreover, Everson pointed out, “AI agents are always on.” Especially if those agents are ranging across a globally (or even regionally) deployed network, this would seem to particularly impact WAN architectures and budgets, requiring bigger pipes running at peak utilization most or all of the time.
- The result, according to Everson: “Traditional planning assumptions (e.g., burstiness, downlink dominance, human-paced interactions) will need to adapt to the new reality of AI and agentic AI traffic that lasts longer, demands more upstream capacity, and operates at software speed.”
- Real-time communications traffic may have to compete with AI-based traffic for network priority. “AI inference paths will also become strategic network assets, requiring high levels of resilience, observability, and differentiated treatment (e.g., Quality of Service (QoS) and path security),” Everson told the committee.
So not only will your enterprise be running a much bigger, more complex network, with even more competition among traffic types, but uptime will be that much more critical, too. Where you use cloud services, your provider’s track record on outages will need severe scrutiny. And you’ll need to understand the effects of network downtime on your enterprise’s unique constellation of AI agents, based on those agents’ behavior and requirements for access to the various resources they draw upon. A formidable task lies ahead.
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