AI is exposing the limits of traditional network architecture
AI Summary
AI advancements are challenging traditional network architectures due to the unpredictable traffic generated by continuous inference and agent-to-agent communication. Organizations must reassess long-standing assumptions as AI systems become integral to operations, highlighting the network's role in performance and reliability.
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Presented by Tata Communications Continuous inference, agent-to-agent communication, and real-time data pipelines are generating unpredictable, always-on traffic that legacy architectures were never built to support. As AI moves from pilot project to operational backbone, the network is emerging as a critical control layer that determines performance, reliability, and cost. The shift is forcing organizations to question assumptions that have held for decades. Legacy systems were static and ri
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