
“When AI pipelines slow down or traffic overloads common infrastructure, business processes slow down, and customer experience degrades,” Kale says. “Since many organizations are using AI to enable their teams to make critical decisions, disruptions caused by AI-related failures will be experienced instantly by both internal teams and external customers.”
A single bottleneck can quickly cascade through an organization, Kales says, “reducing the overall value of the broader digital ecosystem.”
In 2026, “we will see significant disruption from accelerated appetite for all things AI,” research firm Forrester noted in a late-year predictions post. “Business demands of AI systems, network connectivity, AI for IT operations, the conversational AI-powered service desk, and more are driving substantial changes that tech leaders must enable within their organizations.”
And in a 2025 study of about 1,300 networking, operations, cloud, and architecture professionals worldwide, Broadcom noted a “readiness gap” between the desire for AI and network preparedness. While 99% of organizations have cloud strategies and are adopting AI, only 49% say their networks can support the bandwidth and low latency that AI requires, according to Broadcom’s 2026 State of Network Operations report.
“AI is shifting Internet traffic from human-paced to machine-paced, and machines generate 100 times more requests with zero off-hours,” says Ed Barrow, CEO of Cloud Capital, an investment management firm focused on acquiring, managing, and operating data centers.
“Inference workloads in particular create continuous, high-intensity, globally distributed traffic patterns,” Barrow says. “A single AI feature can trigger millions of additional requests per hour, and those requests are heavier—higher bandwidth, higher concurrency, and GPU-accelerated compute on the other side of the network.”




















