The AI-native buzzword sounds scary because you read it as "AI eats your packets," but the engineering plan is a lot more down-to-earth. They want to feed the schedulers sanitized telemetry (per-slice latency, packet loss, active UE count) into trained controllers instead of hand-tuned heuristics so the slice can rebalance in milliseconds.
The critical safeguard is to separate that telemetry plane from any user payload and run it through a zero-trust gateway before the ML model sees it. We built the same trick into a 5G edge orchestrator last year and the model only ever touched aggregated KPIs, never user content, which kept compliance teams happy while still letting the scheduler react faster than timers ever could.
The critical safeguard is to separate that telemetry plane from any user payload and run it through a zero-trust gateway before the ML model sees it. We built the same trick into a 5G edge orchestrator last year and the model only ever touched aggregated KPIs, never user content, which kept compliance teams happy while still letting the scheduler react faster than timers ever could.
"AI" and trustworthy in the same sentence.
They must think we're stupid.