Telecom operators are experimenting with AI across billing, support, churn prediction, and personalization. Some say it’s just hype, while others see it as the missing link to scale.
Where do you see AI in telecom making a real impact today (billing automation, predictive support, personalization, etc.)—and where are the biggest gaps (legacy systems, data quality, ethics)?
Do you think AI will become foundational to the telecom stack, or will it remain a set of bolt-on tools?
My greatest trouble as the topic is concerned is, will this not reduce job opportunities in the nearest future and is telecom not too much becoming IT
AI is definitely showing value in telecom through billing automation, churn prediction, and customer personalization. But the gaps—especially legacy BSS/OSS systems and poor data quality—still slow down adoption. From what I’ve seen at TelcoEdge Inc, AI delivers the most impact when integrated with cloud-native BSS, OSS, and edge-driven platforms rather than just added as bolt-on tools.
Do you see AI in telecom more as an operational efficiency driver, or as a foundation for new revenue models like IoT and enterprise services?
Absolutely agree. AI is proving its value when embedded within cloud-native BSS/OSS and edge architectures, rather than added as a standalone layer. Companies like Nokia, Amdocs, Ericsson, and Telco Edge are showing how integrated AI and network intelligence can unlock predictive operations and new monetization models — moving beyond efficiency toward true service innovation.
Interesting points — never heard of TelcoEdge Inc before. Looks like I’ve got some reading to do… or a new tech rabbit hole to fall into 
Thanks, that makes a lot of sense! Really interesting to hear how AI is moving from “bolt-on” to core, and how companies like TelcoEdge are shaping that shift.