How Deutsche Telekom uses AI

Deutsche Telekom's RAN Guardian Agent, built with Gemini models on Google Cloud, went live in its German mobile network in November 2025. It is a multi agent system: one agent finds upcoming public events from public sources, another assesses whether nearby cells can carry the expected traffic and monitors them live, and a third executes corrective actions such as reallocating resources or adjusting configuration, documenting every action. It is being extended to the Czech Republic and Croatia. In February 2026 Deutsche Telekom announced MINDR, which applies the same approach end to end across radio, transport and core domains, with first production releases planned for later in 2026.

• Cycle time reduction: at least 95%, live operations, major events

  "And in live operations it has reduced the time needed to manage major events from hours to around a minute, a more than 95% improvement."

  Claimed by: organization
• Interactions handled: at least 100, first month after launch, Christmas market events

  "Since its launch in November 2025, RAN Guardian Agent has autonomously triggered over 100 remediation actions at Christmas market events during its first month."

  Claimed by: organization

Deutsche Telekom uses a family of UneeQ digital humans that speak German and guide customers to products: Selena explains home broadband options after asking about the customer's home and lifestyle, Max answers customer questions on the Telekom website and app, and Mia works at events such as MWC. The vendor presents them as a way to give hesitant customers confidence in technical purchases. The case study shows conversion, cart abandonment and rating tiles without readable figures, so no metric is recorded. The case study does not describe screens in Telekom shops; the kiosk channel reflects Mia's use at events.

No outcome disclosed.

Deutsche Telekom's own newsroom describes a pilot, first run in Bornheim near Bonn, in which a measuring vehicle with 360 degree cameras and laser scanners collects environmental data for its FTTH rollout, and software developed with Fraunhofer IPM automatically classifies around 30 categories of surface and obstacle (pavement type, trees, root structure) to determine the optimal cable route, which a Deutsche Telekom planner then checks and approves. A separate account from Fraunhofer IGD's Steep workflow platform, which has processed this imagery and point cloud data at scale in Deutsche Telekom's cloud since the collaboration began in 2017, says the program has since planned more than 10 million households and connected more than 8 million of them to FTTH, and that planning and approval work which used to take several months is now finished within a few weeks, on average about 75% faster. Steep credits that speedup to the whole geospatial data infrastructure it built for Deutsche Telekom, including large scale point cloud classification and the Fibre3D tool that lets planners present plans to municipalities with fewer site visits, not to automated AI route determination alone: Steep says the classification output "can later be used to automatically determine optimal routes", describing that as a future use rather than a capability it says is running at this scale today.

• Cycle time reduction: about 75%

  "Now they are on average about 75% faster and can be finished within a few weeks."

  Claimed by: vendor