How AI is transforming network incident response (and where it still falls short)

If you’ve sat through any vendor pitch in the last year, you’ve heard the promise. AI will detect the anomaly, correlate the signals, identify the root cause, maybe even remediate it. The autonomous network operations center is just around the corner. I’ve spent close to a decade building anomaly detection and telemetry systems at scale, and I think that promise is partly true, partly aspirational and partly misleading. The reality is messier. AI is genuinely helping in a few specific places, and it’s nowhere close to delivering in others, mostly for reasons that have nothing to do with model quality. The biggest reason: we still can’t see most of what’s happening on our own networks. The visibility problem comes first Network operators love to talk about observability. The actual state of observability in 2026 is much less impressive than the marketing suggests. According to Broadcom’s 2026 State of Network Operations report , 95% of IT professionals report lacking visibility into net