Europe’s AI Ambitions Grow Stronger, but Adoption Across Key Sectors Still Lags

Artificial intelligence sits at the heart of Europe's digital strategy. The European Union has rolled out one of the world's most comprehensive AI policy frameworks through its Coordinated Plan on Artificial Intelligence, backed by major funding programmes and reinforced by the new AI Act. The goal is clear: make Europe a global leader in trustworthy, human-centric AI while boosting competitiveness and resilience.

But a new OECD assessment shows that, while the strategy is ambitious, real-world adoption remains uneven. Across agriculture, healthcare, manufacturing and mobility, AI is growing, but often in small steps. Many projects remain pilots. In several sectors, AI is used for limited administrative tasks rather than deeply integrated into daily operations.

The foundations are in place. The challenge now is scale.

Smarter Farming, Slower Uptake

In agriculture, AI is often presented as a lifeline. European farmers face shrinking workforces, rising costs and growing climate pressures. AI tools promise more precise, efficient and sustainable farming.

Robots equipped with cameras and sensors can weed fields, spray crops and even harvest produce with minimal human intervention. Predictive models analyse weather patterns, soil data and satellite images to forecast yields or detect disease early. Drones and smart sensors monitor crops and livestock in real time, helping farmers act before small problems become major losses.

This shift towards "precision agriculture" could reduce chemical use, improve productivity and save labour. Yet adoption is uneven. Large farms are leading the way, while smaller farms often lack reliable broadband or the digital skills needed to use advanced systems. High upfront costs also discourage investment.

The technology is promising. The question is how to make it accessible to the many small and medium-sized farms that dominate Europe's agricultural landscape.

AI in Hospitals: Progress with Caution

Healthcare is one of the most dynamic areas for AI in Europe. Hospitals are already using AI tools to support doctors, especially in radiology. Machine learning systems can help detect tumours, fractures and other abnormalities more quickly and consistently.

Beyond diagnostics, AI is being tested to manage hospital operations. It can predict bed shortages, improve scheduling and reduce paperwork through automated documentation. In pharmaceutical research, AI is accelerating drug discovery by analysing large datasets to identify promising compounds.

Despite these advances, progress is cautious. Health data remains fragmented across countries and institutions, making it difficult to build large, reliable AI systems. Integrating new tools into older IT systems is expensive. Strict data protection and medical device rules, while essential for safety, add complexity.

AI is helping healthcare systems cope with rising demand. But scaling it across Europe's diverse health systems remains a work in progress.

Factories and Transport: Big Potential, Modest Use

Manufacturing is often seen as a natural home for AI. Smart systems can predict machine failures before they happen, reducing downtime. Computer vision tools can spot defects on production lines faster than the human eye. AI can also optimise supply chains by forecasting demand and managing inventory more efficiently.

Yet adoption is still modest. Many companies use AI mainly for office tasks such as text processing, rather than embedding it deeply into production. Smaller firms often lack the expertise to customise AI tools to their needs. Legacy systems and fragmented data slow integration.

In mobility, AI underpins automated driving, smart public transport systems and freight optimisation. European start-ups are developing innovative solutions, from traffic management tools to electric fleet monitoring. But overall uptake in the transport sector lags behind more digital industries. Data sharing challenges, infrastructure gaps and limited investment hold the sector back.

The potential is undeniable. The rollout remains cautious.

The Roadblocks Europe Must Clear

Across all four sectors, similar barriers appear. High upfront costs make AI investments risky, especially for small businesses. Broadband connectivity is still uneven, particularly in rural areas. Data are often siloed and incompatible, limiting their usefulness. Most importantly, Europe faces a shortage of AI-skilled professionals who can build, adapt and manage these systems.

The EU AI Act aims to build trust and ensure safety. But compliance can feel complex, especially for smaller organisations. Policymakers now face a delicate balance: maintaining strong safeguards while encouraging innovation and experimentation.

Europe has built a solid AI strategy and a clear regulatory framework. The next step is turning ambition into everyday reality. If the EU can improve infrastructure, boost digital skills and make data more accessible, AI could strengthen farms, hospitals, factories and transport systems across the continent.