AI for fibre
How can artificial intelligence enhance the operational performance of FTTH networks?
This study examines how AI is transforming the performance of FTTH networks in different national environments by addressing structural limitations in planning, quality control, supervision and maintenance. It draws on real-world examples from international operators that have automated part of their processes, as well as an analysis of technology strategies implemented in various markets.
Key questions
- What are the common weaknesses in the FTTH chain, regardless of country or network type?
- How does AI enhance the accuracy, quality of documentation, and operational continuity of the network?
- Which use cases currently deliver measurable gains (planning, QA, supervision, maintenance)?
- How do operators structure their data, workflows and repositories to enable automation?
- What organisational or technological risks need to be managed (dependency, data quality, opaque models)?
- How can AI contribute to the economic sustainability of FTTH, considering increasing volumes, availability requirements, and competitive pressure?
- World
Operators
- CityFibre
- Connect Fibre
- Bouygues Telecom
- Deutsche Telekom
- Brightspeed
- NBN
- KDDI
- China Mobile
- Turkcell
- Verizon
- Etisalat
- Proximus
- Telefónica
Suppliers/technologies
- IQGeo
- Comsof
- EXFO
- Fiber Sense
- ZTE
- Ciena
- AWS
- NVIDIA
- Axis Solutions
- HOC
- Florian Frigo, Consultant