NAN120: How Network Engineers Can Thrive in an AI-Driven World

In this episode, senior solution engineer Ashwin Chosi shares how artificial intelligence is reshaping network engineering at hyperscale providers like AWS and Microsoft Azure. Drawing on his journey from a telecom master’s program to cloud support and WAN backbone teams, he explains that AI is no longer a futuristic add‑on but a necessity for handling the massive inter‑dependencies of modern networks. The conversation highlights the shift from isolated device management to coordinated, region‑wide operations where a single mis‑configuration can cascade across hundreds of services, demanding new guardrails and safety nets.

The discussion then turns to concrete AI benefits. By automating repetitive tasks—such as pulling routing tables from dozens of devices or triaging intermittent tickets—AI frees engineers to focus on high‑impact problems. Advanced correlation engines can map a network incident to its business impact, turning raw telemetry into clear, actionable business cases. This not only speeds resolution but also provides post‑mortem insights that identify single points of failure and guide investment decisions. Importantly, Chosi stresses that AI augments, rather than replaces, domain expertise; human judgment remains essential for complex root‑cause analysis.

Beyond technology, the episode underscores the value of community‑driven learning. Chosi’s "100 Days of Generative AI" series, a searchable web portal and LinkedIn cadence, exemplifies how sharing knowledge accelerates adoption across the network automation field. He advocates a "learn‑by‑doing" mindset: define a real problem, prototype an AI‑powered solution, then share the findings. While AI handles data‑heavy tasks, clear communication and documentation become the differentiators for teams operating at scale. As AI matures, engineers who can translate technical insights into business language will lead the next wave of network innovation.