Deutsche Telekom detailed moves to capitalise on growing demand for sovereign AI services in Europe, setting revenue goals in the millions of euros range as part of broader ambitions involving businesses and public institutions.

The German-headquartered operator believes the European sovereign sector to be a leading opportunity for it outside the US market.

It noted companies and public bodies are keen to reap the automation benefits of AI “while retaining control over data and operations”. Deutsche Telekom stated the sector is “becoming a growth business” and it would continue striking relevant partnerships to tap the rise.

The operator highlighted work to produce an automation platform for small- and medium-sized businesses covering recurring jobs as another AI-related move.

All told, it hopes to book annual revenue of around €250 million from non-US AI activities this year and about €800 million by 2030.

Deutsche Telekom believes the AI opportunities go beyond the obvious, predicting phone calls are set to benefit from the technology in several ways.

It offers a real-time translation service for mobile phone calls, part of an assistant which can also field questions and provide content summaries. Deutsche Telekom believes there is “an opportunity for additional services” and tariffs.

Deutsche Telekom board members are gearing up to explain to investors how its current and future work with AI is creating revenue.

CEO Timotheus Hoettges said the technology presents opportunities around service personalisation, network management and security.

He said it is important the “technology delivers measurable value” across the organisation.

More than 100,000 staff have been trained in using AI for predictive maintenance tasks, while around 2.6 million customers used its chatbot for service queries in H1.

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The usefulness of AI to industries will largely be determined by more traditional factors including investment and appetite for change, the principal architect and field CTO of intelligent data infrastructure company NetApp told Mobile World Live.

Rahul Sharma (pictured) believes AI is at a juncture between initial optimism and business realities, with the latter set to be the primary influence on how the technology impacts industrial digitalisation.

“Early and unbounded enthusiasm has started to give way to a more serious assessment of the cost-benefit of AI.”

Sharma believes the impact of the technology is being felt in industrial settings, but argued “adoption speed, investments, skills, frameworks” and other elements “all determine how this change process evolves”.

Industrial players are now examining how AI can be used to tackle business challenges in a different way, though Sharma emphasised reality is biting as companies find “success in proofs-of-concept has not always translated into true RoI”.

“The make-or-break factor most often is data.”

Sharma notes AI deployments so far typically involve generative iterations and machine learning or model training, with NetApp “seeing significant growth and investment across both domains”.

Generative iterations are helping companies “unlock greater value from their existing data assets”, including those which were previously unseen or underused. “At the same time, machine learning and AI training workloads continue to expand rapidly, particularly in data-intensive industries such as life sciences, financial services, manufacturing and engineering”.

NetApp can offer some racy details of AI data based on work with leading motorsports teams, one of which is the Aston Martin Aramco Formula One team, which picked the company to be its global data infrastructure partner as part of a wider collaborative strategy highlighted during the AMR Technology Forum in July.

Sharma said the team “needs a common and consistent data infrastructure that provides the flexibility and agility to both keep up and take advantage of the AI revolution”.

Adjustments
It is an example of the tailored approach NetApp pitches itself on and one which Sharma uses to hammer home his point about the importance of data, “one of the most critical assets for any organisation”.

The Aston Martin Aramco Formula One Team wants “to deliver unified data wherever it is needed” for management, control and governance purposes.

But Sharma noted data access requirements can create security headaches, particularly in an era where the technology is pushing companies beyond their usual protective boundaries.

It requires built-in security features which enable data recovery and protection “with minimal disruption”.

Companies must also begin to look beyond traditional approaches reliant on “creating and moving multiple copies of data”, Sharma argued, explaining such methods are “no longer efficient” or sustainable compared with a single source approach NetApp developed.

The changing aspect of data access and management means partnerships are becoming an important element. In the case of NetApp, these collaborations span fields including public cloud storage, managed service providers and operators, and companies running so-called AI factories.

Sharma explained the goal is to “help organisations build a consistent data plane that incorporates everything from on-premises to public cloud” and sovereignty services.

He said the company provides “a range of connectivity options” for businesses to access their data, “from internet to private circuits, colocation and hosted or managed services”.

Works both ways
The Aston Martin Aramco Formula One Team is a high-profile example of what companies require of NetApp.

Sharma said the team needs ways to derive insights from “vast volumes of highly valuable data” used to make decisions in real time for areas including race strategy, performance optimisation, predictive maintenance, vehicle design and safety improvements.

It is an environment which represents the very ethos of F1 in terms of pushing the boundaries of engineering and technical abilities, albeit one focused on digital ambitions rather than the sport’s original mechanical goals.

Sharma highlighted the team’s need to handle “trackside operations during a race weekend” along with “engineering and design activities” at its factory as examples.

The work filters down into broader industrial operations in much the same way car technologies proven on the track often feed into road-going vehicles.

Sharma said product lifecycle management and speeding time-to-market are real-world gains the automotive industry stands to gain from NetApp’s work with motorsports teams. He noted digital twin technology is something even sectors including healthcare could benefit from due to the boost to R&D and manufacturing processes.

NetApp’s work with the Aston Martin Aramco Formula One Team is not a one-way street. Sharma said the collaboration is driving developments including recent investments in “universal data processing engine technology”, which positions the company for increasing use of AI in the racing series and beyond.

“The ability to leverage accelerated computing with GPUs and CPUs at the storage layer is something that customers like Aston Martin Aramco Formula One Team and others will be able to benefit from immensely as they extract value from their full data estate.”

Sharma predicts further benefits of the approach to be felt when F1 regulations change in 2028, a shift he expects to unlock “increasingly sophisticated adoption of AI and GPU” technologies throughout the sport.

But he emphasised other industrial sectors also stand to benefit from NetApp’s work, because it is already providing the ability to optimise AI training and inferencing by “selectively moving only the most relevant datasets to the public cloud”.

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