Bloomberg Intelligence
This article was written by Bloomberg Intelligence Senior Industry Analyst John Butler and Associate Analyst Hunter Sacco. It appeared first on the Bloomberg Terminal.
AI poised to transform telecom customer care, network operations
Artificial intelligence has the potential to lower wireless carriers’ costs, with T-Mobile parent Deutsche Telekom seeing a 20-30% productivity gain in customer care and network operations, possibly offering a blueprint for US operators. The technology is being deployed in the customer-care operations of the three leading US carriers, with T-Mobile appearing to have an early lead in using AI to improve network-capacity planning.
AI makes first mark in customer care
Wireless carriers have initially deployed AI in their customer care units to simplify their often complicated service plans and aid in transactions. They’re deploying the technology to answer questions with chat bots and may soon be able to use it to guide subscribers through complex plan line-ups, features and pricing to determine their best option. Marketing departments are using AI to tailor promotions to the local level, which should boost marketing efficiency and potentially reduce churn.
The carriers are also using AI to gather subscriber data that customer care reps can use to enhance service and drive cross-selling. Chat bot technology might advance to the point where it replaces live agents, though this application is likely a few years out.
AI promises to lower operating costs
The leading US telecoms have yet to quantify the potential cost savings from the deployment ofAI in their customer care and network operations. But Deutsche Telekom CEO Tim Hottges said at the company’s 2024 capital markets day that he sees the potential for a 20-30% productivity gain in migrating to an AI-driven autonomous network. He expects a similar-sized benefit in the company’s software-development and sales and customer-service units. Hottges estimates that Deutsche Telekom could cut 10% of its contract analysis and legal costs with AI.
Though many of these applications need to be planned and implemented, it’s likely that US carriers could realize significant cost savings by streamlining their operations and automating radio-access networks.
AI set to automate radio access networks
Artificial Intelligence could generate significant energy and other cost savings for carriers by allowing them to automate their radio access networks with AI RAN. Currently, the bandwidth in a wireless network is over-provisioned to ensure high quality of service for users, which creates idle capacity when very little is needed at certain times during the day, such as the early morning hours. The use of AI in a wireless network could yield significant cost savings by shutting down capacity when it’s not needed. Carriers could also reallocate this bandwidth for a different purpose, like Mobile Edge Compute.
Beyond network operating cost savings, AI can also be used for predictive maintenance, network security, service provisioning and a range of other applications.
T-Mobile leads peers in implementing A
T-Mobile stands out from peers in its use of AI to manage network capacity and support new services, suggesting it may be among the first to realize sizable financial benefits. It’s partnered with Nvidia to establish a simulation lab to develop new AI-based radios that fuse wireless and AI computing on a single platform with extremely low latency. The goal of the project is to allocate idle compute power in the network toward new services.
T-Mobile is also using AI to improve its capacity planning by setting up 4 million, 165-meter-wide hexagons across the US to measure usage and coverage to help inform its network build plans. It’s also using AI to arm contact center agents with customer data to enhance interactions and ultimately direct the agents on what the next best action is for the customer.
AI not a big part of Verizon or AT&T’s narrative yet
Like its peers, Verizon is using AI in its customer care centers to route calls to the best agents and to analyze over 800 data points per call to reduce the duration of service calls and boost satisfaction rates. Beyond this, the company doesn’t appear to be very far along in deploying AI in its network operations. Instead, it’s largely promoted its ability to monetize growth in AI traffic loads through Mobile Edge Compute and its fiber network.
AT&T is using AI to significantly reduce call volumes in its contact centers, with plans to expand its use in this setting as it gains more experience with AI. In AT&T Labs — formerly Bell Labs –it’s evaluating ways to implement AI to enhance network efficiency and improve security. Still, we think AT&T and Verizon both trail T-Mobile in their implementation of AI.
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