Telecom operators are moving agentic AI from pilots into daily network work. During a recent FutureNet webinar, Orange, Telenor and Vodafone shared clear priorities. They want faster operations, but also better customer results.
The discussion placed root-cause analysis near the top of the list. This means finding the real source of a network fault. Today, engineers may spend hours tracing complex service issues.
Thomas Nilsson, chief product officer at Polystar, called root-cause analysis a “key area”. He said AI agents can identify problems in minutes. That speed can reduce downtime and protect service quality.
Afnan Ahmed of Telenor supported that view. He said he agreed with the “gold medal from [Nilsson] on cause analysis. It’s probably something that would help a lot in the near term.”
However, the panel pushed the debate beyond basic efficiency. Faster troubleshooting matters, but it does not define success alone. Operators now want automation to support revenue, loyalty and trust.
Alexis Koalla of Orange said operators must link network data to business goals. “The key challenge is how to translate these technical KPIs into business outcomes,” Koalla said. KPIs are performance measures, such as fault rates and repair times.
That shift matters for customer-facing services. If AI detects faults earlier, users see fewer disruptions. If teams respond faster, customers receive more reliable broadband and mobile service. That can improve satisfaction scores and reduce churn.
Mabel Pous Fenollar of Vodafone stressed the same point. She said ensuring that “the experience to the customer is better is super essential to us.”
The panel also discussed fiber break coordination. These incidents often require several teams and suppliers. Agents can contact the right people, track actions and support service-level commitments.
According to Fenollar, “when you have a fiber break and you need to coordinate and ring different teams, agents play a pivotal role there.”
Detection also emerged as a strong use case. Koalla said, “Detection with a good level of accuracy from agents could be a very good thing for network operation.” Better detection can reduce alarm noise and focus engineers on real problems.
Still, the move will not be simple. Telcos need cleaner data, stronger governance and new operating habits. They also need staff who can manage automation safely.
“We are moving from pure network operations engineers to what we call network automation engineers in the operational side of things,” Fenollar said.
For operators, the message is clear. AI agents can help networks run faster and smarter. Yet the larger prize is customer value. Telcos that connect automation to business outcomes may gain a stronger future position. Those that treat it only as cost reduction may miss the wider opportunity.
