AI for predictive network maintenance in telecom

Telstra's SmartFix system is embedded in its network operations and automatically fixes many issues before customers notice a problem. Telstra reports the number of proactive actions it performed in FY25 and says they prevented nearly 1 million support calls. The blog post is part of Telstra's description of its wider AI program and gives no detail on the models or the types of fixes.

After a two year production trial on the French backbone, Orange Global Network and an SD-WAN network, Orange added the Augtera Network AI platform to its NOC tools. Topology based auto correlation groups alarms so operations experts see far fewer of them, and anomaly detection on metrics and logs flags weak signals so incidents can be handled before customers notice.

Orange and Augtera say the correlation will cut the daily number of alarms the NOC has to address by 70%, presented as the expected effect of the rollout rather than a measured result. The integration was due to start in April 2024 in Orange Global Networks, an IP network with thousands of routers in 800 points of presence across 100 countries, with full rollout planned by the end of 2024.

Telkomsel, the Indonesian mobile operator, built an autonomous network capability under its Hyper AI program that lets the network self automate without an engineer identifying the problem first. Two Telkomsel network executives said the system finds customers whose experience has degraded before those customers complain, so the operator can act proactively.

At two high traffic national events the operator named as examples, Christmas and New Year 2023 and Ramadan and Eid, the autonomous network handled thousands of tasks that used to be done manually (a 60% and a 90% drop in manual task volume at each event), resolved them several times faster, and the operator reported fewer customer complaints at both events (down 28% and 22% respectively).

Telkomsel did not publish the total task or complaint volumes the percentages are measured against.

Verizon uses artificial intelligence and machine learning on the 811 call before you dig requests it receives to identify the excavations most likely to damage its underground fiber. The model weighs historical and current activity at the location and the past record of the excavator on site, and high risk digs trigger preventive steps such as extra communication with the excavator. The solution is integrated with Verizon's 811 system; Verizon describes the potential benefit but has not published a measured reduction in fiber cuts.

Grameenphone, Bangladesh's largest mobile operator, handed ZTE full responsibility for its network operations and maintenance in March 2025. ZTE found that wireless faults caused most network incidents and built a pilot with two AI agents, a cross domain fault expert and a wireless fault Copilot, covering more than 4,000 ZTE managed 4G sites. The agents identify faults from live network data, reason over multiple systems to find the root cause, trigger an automatic restart where the equipment can self heal, and otherwise dispatch a work order with the diagnosis to a field technician, who can then query the Copilot on site for the fault history and the fix.

Telefónica España built a network data platform on Microsoft Azure (Azure Data Explorer, Azure Databricks and Power BI) to store and analyse the large volumes of data its 4G and 5G mobile network produces. The team uses it for anomaly detection, to address issues before they affect customers, and for automated network optimization. Telefónica says the project is live with several use cases deployed and that results have been very positive; Microsoft's summary adds substantial savings in operating costs. No figures are published.

TIM Brasil built its own predictive analytics engine to flag developing faults across its mobile access network before they cause an outage, so field crews act preventively instead of reactively. The operator reports the model now supports maintenance prediction across its whole access network, with 85% prediction accuracy, and that corrective interventions to fix network faults fell as they shifted to preventive work. More than a thousand field technicians were trained on the new tools as part of TIM's company wide AI Academy.

KDDI deployed Nokia's AVA Performance Degradation Detection and Resolution (PDDR) solution nationwide to monitor its 4G and 5G radio network around the clock. The model detects performance degradations that raise no alarm, so called silent cells, classifies the likely root cause, and hands recoverable cases to KDDI's own recovery system, which tries to fix them automatically. Recovered cells feed back into the training data. KDDI started on 4G in 2019 and extended the system to its 5G NSA network in 2021.

Vodafone and Nokia jointly developed an Anomaly Detection Service, based on Nokia Bell Labs technology and running on Google Cloud, that detects and troubleshoots irregularities such as mobile site congestion, interference and unexpected latency before they affect customers. After an initial deployment on more than 60,000 4G cells in Italy, it was being rolled out across Vodafone's European network in July 2021, with all European markets planned by early 2022 and plans to apply it later to 5G and core networks. Vodafone expected around 80 percent of its anomalous mobile network issues and capacity demands to be detected and addressed automatically; no measured result was published.