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AI Workloads Are Changing Network Traffic, Is Your Infrastructure Ready?
Have we spent so much time talking about AI models, data, and agents that we've overlooked the networks carrying everything between them? In this episode of IT Infrastructure as a Conversation, I sit down with Jamie Pugh, CTO of Globalgig, to discuss why connectivity is becoming one of the most overlooked challenges in enterprise AI adoption and why network resilience could determine whether AI initiatives succeed or fail.
As organizations distribute AI workloads across multiple clouds, regions, and edge environments, network traffic patterns are changing dramatically. Jamie explains how traditional architectures were built for people consuming applications, while today's AI systems are increasingly driven by systems communicating with other systems. Agents, inference engines, data lakes, and cloud platforms are generating entirely new traffic demands that many existing networks were never designed to handle.
We explore how bottlenecks emerge when enterprises rely on single cloud on-ramps, fragmented connectivity strategies, or network designs optimized for yesterday's workloads. Jamie shares why bandwidth alone is no longer the primary concern, and how latency, carrier diversity, observability, and intelligent routing are becoming business priorities rather than purely technical considerations.
The conversation also examines the growing importance of predictive and self-healing networks, the role of network-as-a-service platforms, and why infrastructure, security, and AI teams can no longer operate in isolation. Jamie offers practical advice for organizations looking to audit their current network readiness and prepare for a future where AI-powered productivity depends on reliable, real-time connectivity.
If AI is becoming part of the infrastructure that powers modern business, what happens when the network underneath it can't keep pace? Join us as we discuss the hidden foundation of enterprise AI and why resilient connectivity may become one of the biggest competitive advantages of the decade. What role do you think networks will play in determining the winners and losers of the AI era? Share your thoughts with me.
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By Neil C. HughesHave we spent so much time talking about AI models, data, and agents that we've overlooked the networks carrying everything between them? In this episode of IT Infrastructure as a Conversation, I sit down with Jamie Pugh, CTO of Globalgig, to discuss why connectivity is becoming one of the most overlooked challenges in enterprise AI adoption and why network resilience could determine whether AI initiatives succeed or fail.
As organizations distribute AI workloads across multiple clouds, regions, and edge environments, network traffic patterns are changing dramatically. Jamie explains how traditional architectures were built for people consuming applications, while today's AI systems are increasingly driven by systems communicating with other systems. Agents, inference engines, data lakes, and cloud platforms are generating entirely new traffic demands that many existing networks were never designed to handle.
We explore how bottlenecks emerge when enterprises rely on single cloud on-ramps, fragmented connectivity strategies, or network designs optimized for yesterday's workloads. Jamie shares why bandwidth alone is no longer the primary concern, and how latency, carrier diversity, observability, and intelligent routing are becoming business priorities rather than purely technical considerations.
The conversation also examines the growing importance of predictive and self-healing networks, the role of network-as-a-service platforms, and why infrastructure, security, and AI teams can no longer operate in isolation. Jamie offers practical advice for organizations looking to audit their current network readiness and prepare for a future where AI-powered productivity depends on reliable, real-time connectivity.
If AI is becoming part of the infrastructure that powers modern business, what happens when the network underneath it can't keep pace? Join us as we discuss the hidden foundation of enterprise AI and why resilient connectivity may become one of the biggest competitive advantages of the decade. What role do you think networks will play in determining the winners and losers of the AI era? Share your thoughts with me.