From reactive networks to AI-driven automation: A new path to network autonomy
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This report explores how a more adaptive, cross-domain AI approach, leveraging the latest AI techniques such as time series foundation models, can move operators forward in their network autonomy journey and unlock significant financial value.
Description
Format: PDF filePages: 23Author: Ayaan PatelPublication date: October 2025
In our latest research, we explore emerging new AI techniques enabling the transition to autonomous networks.
Table of contents
- Foreword
- Methodology
- Editorial independence
- Executive summary
- Introduction
- By moving beyond traditional AI, the average telco can unlock USD800 million value p.a.
- Dual intelligence AI unlocks value through opex and capex savings in addition to revenue gains
- Opex savings are driven by improvements in process efficiency
- Tracking USD800 million across Day 0, 1 and 2 of the network management lifecycle
- Day 0 – Intelligent planning to set the foundation
- Day 1 – Accelerating deployment with smarter AI integration
- Day 2 – Operational excellence and continuous optimisation
- Future revenue opportunities: How dual intelligence AI gains in importance
- Unlocking efficiency in data centre expansion and sovereign cloud integration
- Delivering personalised and programmable networks through private 5G and network slicing
- Recommendations
- Appendix
Technologies and industry terms referenced include: agentic AI, AI, analytical AI, automation, digital twin, dual intelligence AI, efficiency, IBM, intent-driven networks, Machine Learning, network autonomy, Network Management, new revenues, reasoning AI, Telefónica, TELUS, time series foundation model
