Over the past two years, Europe has fundamentally reshaped its approach to artificial intelligence. Governments have introduced national AI strategies, the European Union has implemented the AI Act, billions of euros have been committed to AI infrastructure, and initiatives such as InvestAI and the EuroHPC AI Factories are laying the technological foundations for the continent’s digital future.
Much of this investment has been driven by a common objective: ensuring Europe remains competitive in a global AI landscape increasingly shaped by the United States and China. The conversation has largely centred around sovereign AI, computing capacity, semiconductor supply chains and digital resilience, while more recent discussions have expanded to include workforce readiness and the growing demand for AI talent.
These investments represent an important first step. However, as Europe’s AI ecosystem continues to mature, policymakers, economists and business leaders are beginning to focus on a different question.
How will these investments translate into measurable economic value?
The next phase of Europe’s AI journey will not be defined solely by how much capital is invested, but by how effectively artificial intelligence improves productivity, strengthens industries, accelerates innovation and contributes to long-term economic growth.
From AI Investment to Economic Growth
Artificial intelligence is increasingly being viewed as an economic growth engine rather than simply another wave of technological innovation.
According to Philip Lane, Chief Economist of the European Central Bank (ECB), widespread adoption of AI could increase labour productivity across the euro area by more than four percentage points over the next decade. Even under more moderate adoption scenarios, productivity gains could still exceed 1.5 percentage points, making AI one of Europe’s most significant long-term economic opportunities.
The ECB notes that these gains will depend largely on the pace at which businesses integrate AI into their operations, redesign workflows and equip employees with the skills needed to work alongside these technologies. In other words, investment in AI alone is unlikely to generate economic impact unless it is accompanied by widespread adoption and organisational transformation.
This distinction is becoming increasingly important. While much of the public discussion has focused on AI models, infrastructure and regulation, economists are paying closer attention to a different measure of success: productivity. Historically, productivity growth has been one of the strongest drivers of economic expansion, improved living standards and international competitiveness. AI has the potential to become one of the most significant contributors to productivity growth over the coming decade, but only if organisations move beyond experimentation and successfully embed AI into day-to-day business operations.
Europe’s Adoption Challenge
The availability of AI technologies is increasing rapidly. Adoption, however, is progressing at a different pace.
According to Eurostat, only 13.5% of European enterprises used artificial intelligence technologies during 2024. Adoption was significantly higher among large enterprises, while small and medium-sized businesses (representing more than 99% of all businesses in the European Union) continue to adopt AI at considerably lower rates.
This gap matters because SMEs account for a substantial share of Europe’s employment, innovation and economic output. If AI adoption remains concentrated within larger organisations, much of Europe’s economy may struggle to realise the productivity improvements projected by economists.
The European Commission has repeatedly highlighted this challenge through its Digital Decade objectives, recognising that accelerating AI adoption across businesses of all sizes will be essential if Europe is to strengthen its global competitiveness.
The discussion is therefore beginning to shift from access to AI technologies towards practical implementation. Organisations are increasingly asking how AI can improve operational efficiency, reduce costs, enhance customer experiences and create new revenue opportunities rather than simply introducing AI as another digital initiative.
Commercialisation Is Becoming the Next Competitive Advantage
Europe has long been recognised as a global leader in scientific research, engineering excellence and advanced industrial innovation. Many of the world’s leading discoveries in robotics, advanced manufacturing, healthcare technologies and climate innovation originate from European universities, laboratories and research institutions.
The challenge has often emerged later in the innovation cycle.
Transforming research into globally competitive businesses has historically been more difficult.
According to the European Central Bank, only around 3% of global AI patent families originate from the euro area, compared with approximately 9% from the United States. The ECB also estimates that European companies pay around €250 billion every year in royalties to foreign patent holders, highlighting Europe’s continued dependence on technologies commercialised elsewhere.
This does not suggest a shortage of innovation.
Rather, it highlights the importance of strengthening Europe’s ability to commercialise research, scale technology companies and accelerate the adoption of AI across established industries.
Increasingly, competitiveness is being measured not only by the quality of innovation produced, but by the economic value created from that innovation.
AI Is Moving Beyond Pilot Projects
One of the defining characteristics of the current AI market is the shift from experimentation towards enterprise-wide deployment.
Over the past two years, organisations across Europe have tested generative AI through pilot programmes, internal productivity tools and customer-facing applications. Many of these initiatives demonstrated promising results, but scaling them across large organisations presents a different challenge altogether.
According to McKinsey’s State of AI research, companies generating the greatest value from AI are those integrating the technology into core business functions rather than treating it as isolated innovation projects. These organisations are redesigning workflows, adapting operating models, investing in workforce capabilities and embedding AI into strategic decision-making.
This trend is increasingly visible across Europe.
Manufacturers are using AI to improve predictive maintenance, optimise production lines and strengthen quality control. Healthcare providers are expanding AI-assisted diagnostics and clinical decision support. Energy companies are improving grid management and forecasting through AI-powered analytics, while financial institutions continue deploying AI across fraud detection, risk management and customer engagement.
The conversation is therefore becoming less about whether organisations should adopt AI, and more about how they can deploy it responsibly, securely and at scale.
Policy Is Beginning to Reflect This Shift
European policymakers are also adjusting their priorities.
Much of the early policy agenda focused on regulation, ethics and establishing trustworthy AI frameworks. These remain important, particularly following the implementation of the EU AI Act.
However, recent initiatives demonstrate an increasing emphasis on deployment and competitiveness.
The European Commission’s AI Continent Action Plan and Apply AI Strategy place greater attention on accelerating AI adoption across strategic industries including manufacturing, healthcare, energy, defence and public administration. Alongside continued investment in AI Factories and supercomputing infrastructure, these initiatives aim to reduce barriers preventing organisations from deploying AI more broadly across the economy.
The direction is becoming increasingly clear.
Europe is moving from creating the conditions for AI adoption towards ensuring those investments generate measurable economic outcomes.
Where This Converges: GITEX AI EUROPE
The evolution of Europe’s AI strategy is reflected in the conversations taking place across GITEX AI EUROPE. While discussions around infrastructure, regulation and talent remain fundamental to the continent’s AI ambitions, increasing attention is now being given to commercialisation, enterprise adoption and measurable business impact. As startups, enterprises, investors and policymakers gather in Berlin, the focus is expanding beyond what AI can do to how organisations can deploy it successfully across industries.
This shift creates new opportunities for every stakeholder within the AI ecosystem. Startups are increasingly developing solutions that solve practical business challenges rather than demonstrating technology in isolation. Enterprises are looking for proven use cases capable of improving productivity and accelerating digital transformation. Investors are placing greater emphasis on scalable business models and commercial traction, while governments continue exploring how AI can strengthen public services, industrial competitiveness and long-term economic growth.