Which technologies will shape 2026

Where is cloud headed

The phase when cloud was seen as a buzzword or a disruptor of traditional IT is behind us. Today it’s the platform that powers most digital innovation — new applications, data integration, and the first generation of AI services. According to Gartner analysts, the current stage is moving into a third phase: cloud is becoming a business necessity.

Within a few years, the vast majority of new digital workloads are expected to run on cloud-native platforms. Environments outside the cloud will therefore increasingly be labeled “legacy.” This goes hand in hand with the rise of hybrid and multi-cloud approaches. Companies will combine hyperscalers, local providers, and their own data centers depending on what makes the most sense in terms of performance, cost, legislation, and support. 

Silicon evolution

At the heart of all hardware is still the silicon chip. In 2026 we’ll start seeing a new generation of processors manufactured on so-called 2nm nodes. This doesn’t mean a transistor literally measures 2 nanometers — it’s a marketing label for a generation, not an exact dimension. Even so, we’re operating on the scale of tens of atoms, continuing to increase chip density and efficiency. 

Major players are already reserving most of TSMC’s 2nm capacity for upcoming mobile and PC chips. The goal is higher performance per watt — a key metric for phones and laptops, but especially for data centers and AI clusters. 

Behind this evolution stands a quiet “triumvirate”: IMEC (research and development of new transistor structures), ASML (EUV lithography machines), and TSMC (mass production). Together they keep Moore’s Law moving forward, even as we hit physical limits. In practical terms: cutting-edge silicon will keep getting more powerful — but also rarer and more expensive. All the more reason to know where you truly need it, and where solid “mainstream” hardware in a well-designed cloud is enough. 

Data sovereignty

Data sovereignty is no longer a theoretical debate, but a very practical question: whose infrastructure is our business running on, and under which legal framework can data be handled?

Volatile geopolitics and regulatory concerns are the main reasons European organizations want to reduce their dependence on providers headquartered in the US — especially since US laws such as the CLOUD Act can compel companies to disclose data stored even outside the United States. For European businesses and institutions, this raises compliance challenges and sovereignty concerns (who can access data, under which jurisdiction it falls, and who can legally act on it). For Europe, there’s also a long-term goal: catching up on technological debt and building a stronger domestic IT sector. 

In 2026, a complete break from US cloud providers is still unlikely, according to Forrester’s analysis. A more realistic scenario is a gradual shift toward a more sovereign mix: more workloads in European and local clouds, hyperscale where it clearly makes sense. 

Europe’s sovereign ecosystem is strengthening quickly. Players like OVHcloud and Open Telekom Cloud build infrastructure fully under European law. Local providers such as Geetoo also enter the picture, combining advanced technical capabilities with local support. At the same time, “EU-only” offerings from AWS and Microsoft are emerging, aiming to align more closely with European requirements. 

For 2026, the real story will be balancing pragmatism and sovereignty. The typical path won’t be “everything out of US cloud,” but a smart combination of environments with clear governance and an exit strategy. 

From tool to assistant

AI in 2026? Less about polished demos that show benefits in perfectly defined scenarios — and more about real impact on day-to-day operations. The expected era of agents (digital coworkers) is approaching: systems that don’t just answer prompts, but execute tasks. This shift increases requirements for data quality, integrations, and access management. 

Gartner points to two key directions. First: by 2028, more than 60% of enterprise GenAI models will be domain-specific (DSLMs). These models are trained on specialized data for a particular industry or business context, making them significantly more accurate and practical than “general” models. 

Second: Gartner predicts that up to 30% of GenAI workloads will run on-prem or directly on devices (on-device). In practice, that means moving parts of AI closer to where data is created and used — for faster response times, better control over sensitive information, and easier compliance. That’s also why hybrid architectures are gaining momentum: heavy compute and scaling in the cloud, while real-time decisioning and sensitive processing happen locally, where it makes the most sense. 

Predictive cybersecurity

The attack surface is expanding. AI-powered cyberattacks target applications, networks, and IoT systems. Security therefore can’t be only about detection and response. Prevention will be critical: attack simulation, deception, predictive protection, and minimizing room for human error. Gartner calls this approach Preemptive Cybersecurity (PCS) — security that uses advanced AI techniques to anticipate, disrupt, and neutralize attacks before they happen. Gartner also notes that by 2029, technology products lacking preemptive cybersecurity will lose market relevance, as proactive defense becomes a universal requirement. 

Quantum computers, the “end of smartphones,” and data centers in orbit

Quantum computing is one of those innovations that feels closer every year — yet it hasn’t truly entered mainstream practice. Once we solve the operational complexity (for example, stable qubits outside lab conditions) and develop resilient algorithms that can cope with decoherence, we may finally move from labs into the real world. That could trigger a genuine revolution across industries, because for selected problem types, quantum computers could outperform today’s most advanced supercomputers by a wide margin. 

At the same time, we’ll need to prepare for a new era of cybersecurity. Quantum computers could eventually undermine parts of today’s encryption. And at least at first, quantum won’t be “on-prem” — we’ll consume it as a service, something hyperscale providers are already building toward. That sets up a new cloud battleground: who will deliver the best services and interfaces to help businesses take their first quantum steps. 

Blíží se konec chytrých telefonů? Sam Altman z OpenAI a Jony Ive, bývalý dvorní designér společnosti Apple, chystají nový AI hardware. Zatím není zcela jasné, jakou bude mít funkcionalitu. Mluví se o kapesním formátu bez displeje. A podle prvních náznaků má jít o „anti-iPhone“: jednoduché zařízení, které nebude stát na nekonečných notifikacích a scrollování, ale na klidnějším používání a větší důvěře v to, že AI za vás část věcí odfiltruje a vybere správný moment, kdy vás vyrušit. 

Cloud and AI demand ever more compute and therefore more data centers. But building new data centers today isn’t just about buying servers: it’s land, permits, infrastructure, and energy, and the whole process can take years. That’s why some players are looking upward, literally.

Startup Aetherflux has announced plans to launch its first “data center satellite” within two years and offer AI compute capacity from orbit, powered by solar energy, to bypass terrestrial construction and energy constraints. It sounds like sci-fi, but it captures the reality of 2026: the race for compute is also a race for energy and data center capacity.