Orange Says Messy Data Is Slowing Network Automation

Orange is still chasing its goal of an autonomous "AI brain" to run its network, but the project is taking longer than planned because the data feeding that brain is too inconsistent. Chief technology and innovation officer Bruno Zerbib told Light Reading that mismatched, incomplete or low‑quality data across systems is now one of the main barriers to deeper automation.

Instead of a single, clean view of the network, Orange faces multiple data sources that do not always line up. That makes it harder to train AI models, automate operations and safely hand more decisions to software. Until the operator can standardize and reconcile this data, the vision of a truly self‑driving network will remain out of reach.