Deutsche Telekom is using AI both to improve internal operations and to sell AI services to businesses. The company has named practical uses in customer service, hardware maintenance and network management, and it has set ambitious group-wide efficiency and growth targets. But its published figures do not isolate how much cost reduction or revenue growth AI itself has delivered.
How Deutsche Telekom expects AI to improve efficiency
The company frames AI as one part of a broader operating model that also includes digitization, automation, shared platforms and global scale. Its strategy is not that AI alone will produce growth: management has identified several efficiency levers, including more efficient fiber rollout, a shared European operating model and reductions in shared functions. (Deutsche Telekom’s 2024 strategy announcement)
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Customer service and employee support
Deutsche Telekom identifies automating customer service as one way to improve efficiency. It also launched AskT, an internal chatbot, in 2024 and expanded it internationally, including to Greece and Hungary, in the first quarter of 2025. The 2025 annual report says AskT draws on internal data and external knowledge, with models including those from UnifyApps and OpenAI. (2025 annual report)
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In a November 2025 employee survey reported in that annual report, 53% said they regularly used AI at work, up 9 percentage points from May 2025. That is an adoption measure; it does not show how much time employees saved or establish a financial return.
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Maintenance and network operations
The annual report says data-based analysis is used to maintain hardware more proactively, understand customer needs and manage networks more efficiently. In a specific network example, Deutsche Telekom says AI can anticipate local demand peaks, such as those around an open-air concert, and increase antenna capacity when needed. It can also put frequencies into sleep mode when demand is expected to be low, aligning network settings with traffic and reducing energy use. (2025 annual report; 2024 strategy announcement)
What financial targets has Deutsche Telekom set?
At its October 2024 Capital Markets Day, Deutsche Telekom set group-level ambitions through 2027, using 2023 figures as the baseline for average annual growth targets. They cover the company’s overall performance—not AI-specific returns.
| Measure | Target through 2027 | Scope and qualification |
|---|---|---|
| Net revenue and service revenue | Around 4% average annual growth | Group ambition based on 2023 figures; not attributed specifically to AI. |
| Adjusted EBITDA AL | 4–6% average annual growth | Group ambition based on 2023 figures; not attributed specifically to AI. |
| Indirect costs as a share of service revenue | Reduction of 3–5 percentage points | Target by 2027 for the group excluding T-Mobile US; not an AI-only savings estimate. |
| Free cash flow AL | Around €21 billion in 2027 | Group ambition; not attributed specifically to AI. |
| Adjusted earnings per share | Around €2.50 in 2027 | Group ambition; not attributed specifically to AI. |
Management listed AI and automation in customer service and operations among several ways to pursue these ambitions. The cost target therefore should not be read as a forecast of savings from AI alone. (Capital Markets Day strategy announcement)
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Rather than relying only on internal efficiencies, Deutsche Telekom is also positioning T-Systems to sell AI infrastructure and services to business customers. Its 2025 annual report names these offerings:
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- AI Foundation Services: a secure environment for developing, testing and running AI applications.
- Business GPT: a business-focused generative AI offering.
- Comind Voice solutions: voice-based AI solutions for business use.
- Industrial AI Cloud: an AI computing service aimed primarily at industrial enterprises in Europe.
The Industrial AI Cloud, developed with NVIDIA and other partners, went live in February 2026. Deutsche Telekom’s annual report says it is powered by around 10,000 GPUs. SAP provides the basis through its Business Technology Platform; the company names manufacturing, financial services and new digital services as potential areas for process applications. These are infrastructure and service offerings, not reported AI revenue figures. (2025 annual report)
At the cloud’s November 2025 launch, CEO Tim Höttges said: “In just six months, we turn an idea into real AI computing power, Made for Germany.” The statement describes the launch timeline and positioning, not a financial result. (Launch announcement, November 4, 2025)
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the reported results do—and do not—show
Deutsche Telekom reported 2025 organic revenue growth of 4.2% to €119.1 billion and organic adjusted EBITDA AL growth of 4.7% to €44.2 billion. Its 2026 guidance included adjusted EBITDA AL of about €47.4 billion. These are company-wide results and guidance; the results announcement does not assign a share of them to AI. (2025 results announcement)
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The company also estimated around €1.5 billion in additional revenue potential across a bundle of products and services, including payment services, device insurance, payment platforms and consumer AI solutions. It did not break that total down by product category or identify an AI-only amount. It would therefore be inaccurate to describe the €1.5 billion as expected AI revenue. (2024 strategy announcement)
Höttges said in the 2025 results announcement that the company is “improving all areas of our business through the systematic integration of artificial intelligence.” That is management’s account of the strategy. The reported financial results show growth across the group, but do not quantify AI’s separate contribution. (2025 results announcement)
Quick Recap
How to assess the AI cost-and-revenue bet
- Internal efficiency: Deutsche Telekom has described uses in customer service, employee support, maintenance and network management.
- Commercial opportunity: T-Systems is offering AI services and infrastructure to business customers, including the Industrial AI Cloud.
- Targets versus results: the cost and growth figures are group-level targets, while the published 2025 results cover the whole company.
- AI-specific return: the company’s cited public material does not quantify realized cost savings or incremental revenue attributable specifically to AI.
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