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Speaking during Deutsche Telekom’s AI Investor Day, John Saw, chief technology officer at T-Mobile highlighted Customer-Driven Coverage (CDC) as one of the company’s biggest AI-driven changes in how it approaches network investment
In sum – what to know
AI guides investment – T-Mobile uses Customer-Driven Coverage to analyze customer behavior and determine where network builds and upgrades could have the biggest customer and ROI impact.
AI protects coverage – Its self-organizing network made more than 30,000 antenna adjustments during winter storm Fern and extended backup battery time by more than 250,000 minutes.
AI scales operations – T-Mobile is using AI to automatically adjust network capacity during major events, with more than 11,000 adjustments made across 12 cities during the recent World Cup.
T-Mobile US is using AI at scale to change how it plans network investment and manages network operations, according to John Saw, the operator’s president of technology and chief technology officer.
Speaking during Deutsche Telekom’s AI Investor Day, Saw highlighted Customer-Driven Coverage (CDC) as one of the company’s biggest AI-driven changes in how it approaches network investment. “Customer-driven coverage is one of the biggest AI lifts in the history of our company and allows us to completely transform the way we think about allocating capital into our network,” he said.
CDC is designed to prioritize network investment according to customer needs rather than simply building for population coverage or geographic area. T-Mobile has mapped the U.S. into millions of 165-meter hexagons, which Saw said provide information about customer behavior in each area.
The data includes dropped calls, data and voice experience, historical churn profiles, acquisition and retention rates, and competitive pressure. T-Mobile then trains AI on that information to determine where the next site build or upgrade could have the biggest impact on customer experience and retention and provide the highest return on investment.
“We then leverage AI, train on all this data to continuously determine where the next site build or upgrade will have the biggest impact on customer experience and customer retention and ultimately giving us the highest return on investment,” he said.
Saw gave Lake Tahoe as an example. Although the area is not densely populated, T-Mobile’s CDC model identified significant visitor traffic from nearby cities including San Francisco, Oakland, and Sacramento. Saw said this resulted in additional investment to provide those visitors with the same network experience they have at home.
T-Mobile is also using AI to respond to network disruptions. Saw highlighted the operator’s self-organizing network, or SON, which automatically adjusts nearby sites when a cell site is lost because of events such as storms or fiber failures.
During winter storm Fern in January 2026, more than 1 million people lost power across the affected areas. Saw said T-Mobile’s SON made more than 30,000 antenna adjustments to keep as many customers connected as possible. The system also adaptively reduced power consumption at cell sites to extend backup battery times by more than 250,000 minutes.
Saw said 68% of T-Mobile customers were able to reconnect service within the first hour of the storm, while 98% were reconnected within the first eight hours. The storm lasted several days and affected 30 states, according to his presentation.
T-Mobile has also expanded its use of AI to manage changes in network demand. Its Dynamic CX capability uses AI to anticipate demand around major events and prepare sites with sufficient capacity, while automatically optimizing the network as crowds and demand shift.
During the recent World Cup in the U.S., Dynamic CX was used in 12 cities and made more than 11,000 automated network adjustments as crowds, performance and demand changed.
Saw also highlighted AI being integrated directly into T-Mobile’s core network, using an agentic AI platform connected to its IMS network to provide services such as live translation.
The broader network strategy includes the operator’s 5G Advanced network and its plans for 6G. Saw said 6G will be AI-native by design and eventually should be able to adapt capacity, latency, and coverage to individual user and application needs.
He said T-Mobile is already using AI across network planning, network operations, and customer services, with the objective of applying AI at scale rather than treating it as a standalone network feature.
Deutsche Telekom CEO: three main AI Investor Day themes
Tim Höttges used Deutsche Telekom’s first AI Investor Day to frame AI around measurable business impact rather than simply technology adoption. He highlighted three questions the company wants to answer: whether telecom can execute AI at scale, whether it can capture value from AI, and how progress and success should be measured for investors and shareholders. Höttges said Deutsche Telekom wants to remain a human-led company while using AI to make customer interactions and internal processes simpler and more efficient. He described AI as a way to redesign the enterprise, including workflows, processes and governance, and said the company has around 500 AI projects underway.
A second major theme was the financial impact of AI and automation. Höttges said Deutsche Telekom expects €1.1 billion ($1.23 billion) in gross savings from AI and automation in 2027, €300 million above its previous €800 million target, and expects €2.5 billion in gross savings by 2030 within its European organization. He also identified €1 billion in additional revenue potential, describing that figure as conservative. Part of that opportunity comes from telecom infrastructure, including planned inference data centers within the telecom infrastructure. Höttges said the company is also targeting 10% to 15% network gross savings and Level 4 autonomous networks.
The third theme was the role of telecom infrastructure in the emerging AI economy. Höttges argued that networks will remain central as AI becomes more distributed across devices, infrastructure, and applications. He highlighted opportunities around inference, latency, and AI capabilities embedded in telecom infrastructure, while also pointing to customer relationships, security, resilience and sovereign infrastructure. He said Deutsche Telekom does not want to compete directly with frontier AI companies but sees an opportunity where trust, sovereignty, and secure access matter.
