Autonomous Network Operations

Autonomous network operations uses digital twins and agentic AI to prevent outages, find root causes, and speed mitigation in large-scale network operations.

Business impact

• WAN bandwidth growth — Google reports that WAN bandwidth grew 7x from 2020 to 2025.
• Outage duration — Protective reroute is reported to reduce outage duration by up to 93%.
• Network scale — The network spans more than 7.75 million kilometers of terrestrial and subsea fiber.
• Network reach — The network connects with more than 5,700 ISPs and partner networks across 200+ countries and territories.

Data requirements

• Network telemetry (tabular) — Needed to observe network state, failures, and performance for autonomous operations.
• Network topology models (tabular) — Used in the digital twin and universal network model representation.
• Traffic and capacity data (tabular) — Used for capacity planning and scaling decisions.

AI methods and techniques

• Digital twin — Used to simulate the network for outage prevention, root-cause analysis, and capacity planning.
• Agentic AI — Used to shorten detection and resolution time for network issues.
• Declarative operations — Business policies are translated into network intent for programmable control.

AI models and model families

Google DeepMind

Industries

Real-world evidence

1 documented case study on record.

Companies using this: Google.