Operations | Monitoring | ITSM | DevOps | Cloud

Last year, Lumen shared its AIOps roadmap. This year: two updates. First, how Lumen's thinking on AI-era org design has shifted — including why the instinct to cut junior headcount is a trap, and what sustainable team structures look like instead. Second, what Lumen built as a result: a single AI core (AskGreg) extended into a customer-facing email agent (NORA), a chatbot, and an in-progress voice agent — all leveraging the same modular platform. Live video demos show the system diagnosing network problems from alarm data and driving real-time network decisions. The closing thesis ties it together.

AI in network operations has moved past the demo. In some shops it's already cutting detection time and clearing the alert noise that used to bury the engineering team. In others, a promising rollout has quietly stalled the moment it met production. That difference between the two rarely comes down to the model, it comes down to how the AI gets integrated into the network and most importantly, the team around it.

Time-series view of how consistently a reservation has been utilized and which resources are consuming it. Makes underutilization or coverage gaps visible at a glance instead of requiring manual investigation.

Alerts when a schedule has been disabled for longer than a set threshold (e.g., 7+ days). Solves the common failure mode where a team disables a shutdown schedule for maintenance and forgets to turn it back on, quietly costing money.