What if your data could act like a brain when combined with smart software? What if every safety-critical decision, every optimization, and every market response took seconds instead of hours, with complete transparency and control? This vision is not a pipe dream. It is turning into reality thanks to agentic artificial intelligence (AI): smart, autonomous systems that not only analyze, but also act. However, before these systems can create real value, a solid foundation is essential.
A recent MIT study shows that 95 percent of pilot projects involving generative artificial intelligence fail to deliver measurable business value. Why? Because most pilots are developed in isolation from operational processes and are not scalable. Many companies experiment with AI on a greenfield site. But let's be honest: the IT landscape of most companies is more akin to the Amazon rainforest in complexity than to a greenfield site. Generative AI tools must therefore be integrated into operational processes. Otherwise, they will not create added value.
Hybrid intelligence may be the solution. This involves master agents controlling the entire enterprise landscape, orchestrating agents that work across platform boundaries - without vendor lock-in, but with maximum security and compliance. Scalability of AI is crucial because companies evolve dynamically: data, processes, and customers come and go. AI systems must adapt to these changes; otherwise, they risk becoming a bottleneck instead of a catalyst.
Orchestrated AI agents must adapt to the dynamic IT landscapes of companies. Otherwise, they risk becoming a bottleneck instead of a catalyst.
Magdalena Jonczak, Senior Vice President, Global Head of AI & Data, T-Systems
To ensure AI moves beyond pilot projects and delivers real business value, it needs a solid foundation built on three pillars:
1. Hosting: The foundation for any AI strategy
Without a robust hosting architecture, AI remains a pilot project with no impact. In industry, data and workloads are distributed across public clouds, private clouds, edge systems, and on-premises systems. Scalable AI needs a platform that connects all these worlds – hybrid and sovereign by design.
With T Cloud, we create exactly that: an architecture guaranteeing multi-cloud freedom, meeting regulatory requirements such as the GDPR, the EU AI Act, and Gaia-X, while delivering the performance needed for computationally intensive applications such as digital twins, physical AI, and agentic AI systems. Hosting is therefore not just infrastructure – it is the strategic enabler of innovation and efficiency.
2. Connectivity: The nervous system of the hybrid world
AI thrives on data. This data must flow quickly, securely, and reliably. In industry, this means 5G campus networks for production sites, global backbones for supply chains, and predictable, consistent latency for real-time decisions. For example, controllers and AI agents in a refinery or a power plant must respond within milliseconds when a valve is opened or closed. If latency is unpredictable, an agent may act too late – posing a risk to safety and production stability.
Connectivity is the nervous system that links edge and cloud, ensuring that agents can respond in the shortest possible time. Without these connections, AI remains blind. With them in place, it becomes a tool that accelerates processes and reduces risks.
3. Cybersecurity: Trust is not optional
With AI adoption, the attack surface increases exponentially. Scalable AI must be secure from the outset – not as an add-on, but as an integral part. This requires zero-trust architectures, continuous monitoring by global security operation centers, and complete auditability of every AI decision.
Especially in the energy industry, where safety-critical processes and regulatory requirements dominate, cybersecurity is a prerequisite for trust. Only when every action is traceable and secure can AI unleash its full potential.
The goal is clear: we must make the leap from isolated solutions and proofs of concept (PoCs) to accountable autonomy – systems that plan, act, and learn. Guidelines as guardrails and human oversight remain essential. And yet the vision unfolds in steps:
Scalable AI requires not only concepts, but also compute power to become a reality. This is where the Industrial AI Cloud comes in – Europe's most advanced AI factory, which we are building in Germany in collaboration with NVIDIA. The Industrial AI Cloud will go live in Q1 2026, just six months from idea to launch.
With the Industrial AI Cloud, companies can not only test agentic AI, digital twins, and physical AI, but also deploy them productively at scale – securely, transparently, and without vendor lock-in. A growing ecosystem of companies is forming, including Siemens, Agile Robots, Wandelbots, Quantum Systems, PhysicsX, and Perplexity. Around 10 companies are already a part of this sovereign AI network.
Europe needs speed, not announcements. The AI factory is our contribution to securing digital sovereignty and industrial competitiveness. Together with customers and partners, we are shaping the future – with infrastructure that combines scalability, security, and innovation.
