Two revolutions are unfolding in parallel: one powered by artificial intelligence (AI) and another by quantum computing.[1] They are at different stages of maturity: AI applications are already gaining traction across industries, while quantum largely remains in the research phase. Yet, both are reshaping what computation means.
Quantum computing is often framed as a radical break from the digital world. But in fact, the traditional computing stack - from semiconductors to the cloud - will continue to handle general-purpose processing, and AI accelerators will dominate pattern recognition and inference. Meanwhile, quantum machines will target the subset of problems where combinatorial complexity overwhelms even the largest supercomputers.[2] This creates new risks and opportunities for Europe.
This post aims to highlight two aspects regarding progress in the quantum industry. First, it outlines in what ways the quantum revolution depends on synergies and parallels with classical and AI computation. Second, it argues that, as in the case of AI, if Europe wants to lead in this field, it must encourage industrial applications.
Synergies and Parallels Across Computational Paradigms
Quantum progress depends as much on algorithms and physics as on existing chip supply chains. This fact has allowed quantum companies to focus on what truly differentiates them, namely, error correction and the creation of stable computational architectures. While classical computing took decades to evolve into the cloud and AI era, quantum is advancing faster because it starts from a far higher technological baseline. At the same time, quantum research increasingly relies on AI to optimise qubit control and reduce error rates. AI models are used to improve hardware calibration, discover new materials for superconducting circuits, and even design novel quantum algorithms.
These facts point to two important aspects. First, the reliance on existing chip supply chains is an opportunity for quantum companies to improve their algorithms, but it also means that the emerging quantum economy is exposed to the same supply chain risks and vulnerabilities as traditional and AI computation. Second, the fact that quantum development is powered by advancements in AI indicates that investments in one can generate higher returns in both, but also that frontrunners in AI are the most advantaged to reap the benefits in quantum, too.
Meanwhile, market trends are paralleling those in AI, with cloud offerings acting as a primary vehicle to diffuse quantum-powered computation. This convergence is particularly visible in business models.
We have entered the era of quantum as a service (QaaS). Here, the goal is not to sell stand-alone quantum machines but to make quantum capabilities available through integrated hybrid platforms that combine classical, AI-accelerated, and quantum resources. Given that today’s chips operate with only tens or hundreds of qubits, much of the near-term value lies in hybrid computing, using powerful classical systems for most tasks while offloading specific optimisation or simulation problems to quantum processors, real or simulated.
This model lowers barriers for adoption, allowing users to access quantum power via the cloud without needing in-house expertise or dedicated hardware. But there is also the risk that QaaS will advantage current, non-EU cloud giants.
Where Does Europe Stand?
In Europe, quantum technologies have become both an opportunity and a test case for the continent’s renewed industrial ambition. The EU combines strong quantum expertise with growing political backing.
According to the Draghi report, Europe hosts the largest pool of quantum-trained experts in the world and a research base that accounts for roughly 16% of global quantum patent families, trailing the US, but still ahead of Japan and China. However, none of the top ten global tech firms investing in quantum are European, with five based in the US and four in China. The US leads through Big Tech–driven deployment and technical advances, while China’s state-backed labs are rapidly catching up. EU firms attract only about 5% of global private quantum funding compared to 50% for US firms. Taking stock of this, the European Commission has recently put forward a strategy to make Europe a global quantum leader by 2030.
According to this strategy, local ecosystems must be ready by the end of the decade. Supply chain chokepoints and a growingly tense geopolitical and geoeconomic landscape naturally force Europe to think in terms of resilience and autonomy. However, as in the case of AI, the problem is that technological evolutions risk being much faster.
If Europe’s strengths lie in science but not in scaling, the policy question then becomes how to translate knowledge into market power.
…And What Can It Do?
Following the innovation literature, an innovation ecosystem is the network of interdependent elements that enable or constrain innovation. It includes the core competencies of innovators (e.g., research excellence), upstream components that supply essential inputs (e.g., cryogenic chips, superconducting materials), and downstream complementors that make technologies usable or valuable (e.g., software and integration services). The EU is strong in the first element and remains dependent on foreign supplies for the second. But to leverage the quantum revolution, the third will be the real game changer.
As in the case of AI, if Europe wants to nurture its quantum power, this is the right moment to pioneer the applications of this technology in the real world, starting from those use cases that hold most promise, from cryptography to navigation, logistics, drug discovery and climate science. Cloud providers are already monetising AI by embedding AI tools and services into their existing cloud offerings. In quantum, the same Big Tech are competing to occupy similar spaces and will probably benefit from established advantages. However, among other pioneers there are also European companies, such as the German-Swiss Terra Quantum, well positioned to minimise external dependencies.
Proceeding pragmatically, Europe should make use of such platforms to integrate quantum computation across industrial use cases. Quantum technology can help optimize innovation and production chains, mapping and updating risks, anticipating climate-induced disasters, enhance cybersecurity, and make machine learning faster and much more efficient. Applying quantum can be the best way for Europe to boost productivity, unlock further innovation, and solve the same problems that are holding it back – securing supply chains, enhancing autonomy and resilience.
End
The fact that quantum is still in its early days as a computational paradigm (and that it will target problems that traditional computing and AI cannot address) suggests that there are strong chances for Europe to remain a serious competitor. By leveraging the first and third element of innovation ecosystems – the expertise and the applications – the EU has a chance to make up for the remaining supply chain risks. In fact, quantum computing will change traditional and AI computation as much as it is affected by them.
We are on the cusp of seeing the accomplishment of a scientific revolution started more than a century ago. Originated in European labs, this can now continue in European markets.
Image source: https://www.tudelft.nl/over-tu-delft/strategie/vision-teams/quantum-computing/what-is-quantum/a-brief-history-of-quantum
[1] Quantum computing is a field of computer science and engineering that applies the qualities of quantum mechanics to solve problems beyond the ability of classical computers.
[2] The foundation of quantum information is the quantum bit, or qubit. Unlike a traditional digital bit that can only represent either zero or one, a qubit can exist in a superposition of both states simultaneously. In a quantum processor, several qubits can also become entangled, forming a collective quantum state. This entanglement underpins the extraordinary computational potential of quantum computers, enabling them to tackle complex problems that classical computers cannot solve efficiently. However, quantum information is extremely fragile and easily disturbed by environmental noise. Because of this, it must be continually stabilized through quantum error correction.
It's interesting how you framed the relationship between quantum and classical computing. The point about quantum relying on existing infrastructure and AI makes perfct sense, you've articulated it so clearly.