Deutsche Telekom partners with McKinsey to scale hyper-personalized agent training with gen AI
Deutsche Telekom· GermanyDeutsche Telekom partnered with McKinsey to build a generative-AI-powered learning and coaching engine to upskill 8,000 human agents in the field and call centers. The team spent six weeks diagnosing agent needs with millions of data points, then four months building and refining the MVP, embedding prompts into agent workflows (e.g. a training video is triggered if an agent struggles with eSIM activation). The likelihood of customers recommending the company increased by 14%.
Overview
Deutsche Telekom partnered with McKinsey to build a generative-AI-powered learning and coaching engine to upskill 8,000 human agents in the field and call centers. The team spent six weeks diagnosing agent needs with millions of data points, then four months building and refining the MVP, embedding prompts into agent workflows (e.g. a training video is triggered if an agent struggles with eSIM activation). The likelihood of customers recommending the company increased by 14%.
The challenge
Deutsche Telekom, which serves 23.5 million private customers, 2.4 million SMEs and 300,000 organizations across Germany with more than 15,000 call center agents and 5,500 field service agents, found that traditional learning programs were not built to meet the individual needs of employees, causing too much variation in performance across service agents and a ripple effect on customer experience, operational efficiency and employee satisfaction.
The solution
Deutsche Telekom partnered with McKinsey and QuantumBlack, AI by McKinsey, applying QuantumBlack's proprietary frontline AI product to build a digital capability model. The team began with a six-week diagnostic phase combining millions of pieces of call data, field service data points, customer feedback and KPIs to identify skill gaps, followed by a four-month MVP phase to build, test and refine the AI-powered learning and coaching engine. The engine was integrated into agents' existing workflows through personal dashboards ("cockpits") that trigger tailored training — for example a training video if an agent struggles with eSIM activation — with supervisors reviewing and validating training recommendations before they reach employees.
Reported business value
Deutsche Telekom's digital-based learning and coaching engine drove a 14-point increase in customers' likelihood to recommend the company (NPS), alongside improved first-time resolution rates year over year, after training an initial round of agents across its field and call-center service lines.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other telecommunications entries in the register.
AI serves QoS & operational efficiency
Orange France deployed AI-based tools across its network operations to improve quality of service and operational efficiency, including the Recovisu diagnostic tool that helps technicians correct errors during interventions, automated frequency declarations with the National Frequency Agency, AI-driven preventive maintenance for equipment such as antenna batteries, and an AI-evaluated citizen infrastructure-damage-reporting app. The NRJ5G app analyzed consumption data to prevent unnecessary mobile site electrical subscription upgrades, saving nearly 48 million.
Orange France· FranceRecovisu · NRJ5GDeutsche Telekom and Google Cloud Collaborate on MINDR Agentic AI for Autonomous Network Operations
Deutsche Telekom, in partnership with Google Cloud, announced MINDR (Multi-Agentic Intelligent Network Diagnostics & Remediation), a multi-agentic AI system built with Google Gemini models on Vertex AI and developed with Google Cloud's Autonomous Network Operations framework. MINDR correlates signals end-to-end across the RAN, transport, and core network domains to proactively identify service-impacting issues and support autonomous, explainable remediation, shifting operations from reactive troubleshooting to predictive automation. MINDR builds on Deutsche Telekom's RAN Guardian Agent, live in production in Germany since November 2025, which monitors network behavior during high-impact events and traffic surges. RAN Guardian autonomously triggered over 100 remediation actions at Christmas market events in its first month and reduced the time needed to manage major events from hours to around a minute (a more than 95% improvement). For 2026 it identified 237,000 events, including around 130 Carnival events each expected to draw over 10,000 participants, served by 611 mobile sites pre-checked for issues; only 5 sites experienced peak loads, which RAN Guardian optimized during the event. RAN Guardian is now scaling across Deutsche Telekom's European national companies, starting with the Czech Republic and Croatia. MINDR's first production releases are planned for later in 2026.
Chunghwa Telecom Builds Multiple Generative AI Solutions with Amazon Bedrock
Chunghwa Telecom, one of Taiwan's largest integrated telecom providers, migrated its generative AI projects to Amazon Bedrock and built three applications: a software development lifecycle documentation assistant, an interactive virtual English teacher using Amazon Titan and Stable Diffusion XL, and a generative AI marketing assistant built on Amazon Personalize.
BT Group writes and maintains 2 million lines of code a year using Amazon Q Developer
BT Group, a UK telecommunications company, rolled out Amazon Q Developer to around 2,000 active developers for AI-assisted coding, chat-based troubleshooting, automated unit test generation, and code transformation from older to newer, more secure versions.
Was this helpful?
Your feedback helps us improve our use case database