EU's €1 Billion 'Apply AI' Strategy: From Regulation to Innovation

The European Union makes a strategic turn: from regulating AI to stimulating AI

The momentum of 2025: why this initiative comes now

The timing of the Apply AI initiative is no coincidence. After the EU AI Act came into force on August 2, 2025, criticism grew that Europe knew how to regulate AI but not how to stimulate innovation. Companies complained about compliance burdens, America and China invested billions in AI development, and European start-ups threatened to relocate to other continents.

The Apply AI initiative is the answer to this criticism. The signal is clear: Europe wants to be not only the regulator but also the enabler of AI innovation.

The six key industries: where the money goes

The Apply AI budget of €1 billion is not distributed randomly. The Commission has identified six sectors where AI can have the greatest strategic and economic impact:

1. Healthcare: AI screening centers and diagnostics

Healthcare receives the largest investment, focusing on AI screening centers for early detection of cancer, cardiovascular diseases, and neurological conditions. These centers combine medical imaging, genetic data, and patient history to identify risks earlier than possible with traditional methods.

Three concrete projects illustrate this approach. The Netherlands-Germany pilot project focuses on AI screening for lung cancer in risk groups, aiming for detection 18 months earlier than current protocols. In Scandinavia, an AI hub is being established for predictive models for cardiovascular diseases, based on a combination of lifestyle data and genetic markers. Finally, a Southern European network is building AI support for diagnosing rare diseases, with pan-European data sharing under strict privacy safeguards.

2. Energy: smart grids and sustainable transition

The energy sector receives investments for AI-powered smart grids that balance supply and demand in real-time, optimally integrate renewable energy sources, and minimize energy waste.

The initiative finances pilots where AI optimizes energy consumption in industrial processes with a target of 15-20% reduction. Additionally, AI is deployed to predict wind turbine and solar panel output, significantly improving grid stability. Finally, AI coordinates demand response programs where households and businesses flexibly consume energy based on availability and prices.

Strategic goal: Europe's ambition to become climate-neutral by 2030 requires intelligent energy systems that can manage the intermittent nature of wind and solar. AI is not a luxury here but a necessity.

3. Automotive: the race for autonomous mobility

European car manufacturers lag behind American and Chinese competitors in autonomous driving technology. The Apply AI program invests in shared testing environments, synthetic data generation for edge cases, and safety validation frameworks that align with EU legislation.

4. Pharmaceuticals: drug discovery and personalized medicine

AI can drastically accelerate the traditional drug discovery process, which averages 10-15 years and costs €2-3 billion. The initiative finances AI platforms for molecular modeling, virtual clinical trials, and personalized medication protocols.

European pharmaceutical giants such as Novo Nordisk, Sanofi, and Bayer collaborate with AI start-ups in projects that identify potential drugs by simulating billions of molecular combinations. These systems can predict side effects before expensive clinical trials begin, saving both time and costs. Additionally, patient populations are segmented for personalized dosing schedules, where AI helps determine which treatment is most effective for which patient.

5. Manufacturing: agentic AI and Industry 5.0

The manufacturing sector receives investments for agentic AI - systems that make semi-autonomous operational decisions within predefined parameters. This goes beyond traditional automation: these AI systems optimize entire production chains, anticipate maintenance needs, and adapt to changing market conditions.

In practice, we see three dominant application areas. With predictive maintenance, AI predicts machine failures 3-6 months in advance, reducing unplanned downtime by 40-50% and dramatically lowering maintenance costs. Supply chain optimization enables manufacturers to adjust production in real-time based on demand forecasts and raw material availability, making the entire chain more efficient. Finally, computer vision systems provide quality control that detects defects completely invisible to the human eye, significantly improving product quality.

The concept Industry 5.0 - humans and machines collaborating in flexible, sustainable production - is central. Europe wants to become a world leader in this, as an alternative to fully automated Chinese factories and American tech giants.

6. Defense: AI for strategic autonomy and cybersecurity

The defense investment is the most sensitive part of Apply AI, but also strategically crucial. The budget goes to cyber threat intelligence, autonomous systems for surveillance and reconnaissance, and AI-supported decision-making in crisis situations.

Technological sovereignty: the geopolitical dimension

The Apply AI initiative cannot be separated from the geopolitical context. Europe is currently heavily dependent on American AI models, with OpenAI, Anthropic, and Google dominating the foundation model market. There's also significant dependence on hardware: many AI chips and components come from Asia, particularly from China. Finally, American cloud providers such as AWS, Microsoft Azure, and Google Cloud control the vast majority of European AI workloads. This triple dependence creates strategic vulnerabilities. What happens if trade tensions escalate? If technology exports are restricted? If geopolitical tensions threaten access to crucial AI capacity?

Balance between openness and protection

A fundamental tension in the strategy is how Europe remains open and competitive while protecting against disproportionate dependence. The Commission seeks this balance through multiple pathways. First, European AI systems build on open standards, with open protocols and APIs that prevent vendor lock-in. Additionally, Europe continues to invest in strategic partnerships with like-minded democracies such as the United States, Canada, Japan, and South Korea, where shared values and norms are central. At the same time, Europe chooses to become a world leader in specific domains such as privacy-preserving AI and trustworthy AI, building on European strengths. Finally, Europe adopts a pragmatic import strategy: not developing everything ourselves, but ensuring alternatives are available for critical components.

Financing structure: how organizations access the funding

The €1 billion budget is not a monolithic pot but consists of different financing instruments:

Horizon Europe AI Partnership (€420 million)

The largest part runs through Horizon Europe, the EU research program. Organizations can apply for project grants for consortia covering at least three member states. Focus is on pre-competitive research and demonstration projects.

Projects are evaluated on scientific excellence and innovation, where fundamental breakthroughs are combined with practical applicability. Additionally, there must be a clear path to market introduction within 3-5 years, ensuring investments actually generate economic impact. Cross-sector collaboration is mandatory, for example between a hospital, an AI start-up, and a university, ensuring complementary expertise. Finally, each project must deliver demonstrable European added value that cannot be achieved through national programs alone.

The first application round opens in December 2025, the second round follows in June 2026.

Digital Europe Programme - AI Testing Facilities (€280 million)

Through the Digital Europe Programme, AI Testing and Experimentation Facilities are funded: physical and virtual environments where organizations can test AI applications without immediate production risks.

These facilities offer access to high-performance computing for training large models, which would otherwise be unaffordable for many organizations. Additionally, participants gain access to realistic test data, both anonymized and synthetically generated, enabling safe testing of AI systems. The facilities have expertise from AI engineers and domain experts who guide teams through implementation. Finally, support is provided for EU AI Act compliance, ensuring organizations develop compliantly from the start.

The facilities are especially intended for SMEs and start-ups that don't have the resources to set up large AI infrastructure themselves. Large enterprises can also participate but pay commercial rates.

National co-funding schemes (€180 million)

Member states match EU funding with national budgets, specifically targeting sectors where they have strategic strengths:

European Investment Bank - AI Scale-up Fund (€120 million)

The EIB offers loans and guarantees for scale-ups bringing AI applications to market. This targets the valley of death - the phase where technology is proven but commercial scaling becomes capital-intensive.

The EIB has clear conditions for this financing. First, companies must have proven product-market fit, meaning the concept has already been validated in practice. The funding may only be used for scaling, not for early-stage R&D - the technology must already work. Additionally, matching private capital is required with a minimum ratio of 1:1, meaning for every EIB euro there must also be one euro of private capital. Finally, the company must commit to a European presence and creating or maintaining employment in Europe.

Critical success factors: why earlier EU initiatives failed

Europe has a history of ambitious technology initiatives that didn't achieve expected impact. Consider Airbus vs. Boeing in AI, where years of investment in aerospace AI delivered limited commercial results. Or Galileo navigation, which struggled with enormous delays and budget overruns. And European cloud projects like Gaia-X, which suffered from fragmentation and lack of adoption. Why would Apply AI be different? The Commission has learned lessons from these failures:

1. Focus on adoption, not just research

Earlier programs mainly financed fundamental research. Apply AI focuses on near-market applications that become commercial within 2-3 years. Each project must demonstrate how it scales.

2. Private sector involved from day one

Projects must have private co-investment. This ensures market validation and reduces the risk of "research for research sake." The minimum private matching is 30% of the project budget.

3. Clear KPIs and milestone-based funding

Funding is released in phases based on measurable milestones. Projects that don't deliver are terminated. This discipline was often absent in earlier programs.

4. Cross-border mandatory but pragmatic

Earlier programs required consortia with 5+ partners from 5+ countries, leading to unworkable structures. Apply AI requires at least 3 member states, but partners must have real added value, not just "flag and pennant" participation.

The balance with regulation: from AI Act to AI stimulation

The Apply AI initiative cannot be separated from the EU AI Act. Critics claimed Europe stifled innovation with rules. This initiative is the answer: regulation and stimulation go hand in hand.

How Apply AI and AI Act reinforce each other

AI Act provides predictability: Companies know within which frameworks they can innovate. This reduces legal uncertainty and makes investments responsible.

Apply AI reduces compliance costs: Testing facilities help companies achieve AI Act compliance without prohibitive costs. This is especially crucial for SMEs.

Together they create European advantage: While other regions struggle with ad-hoc regulation, Europe has both clear rules and substantial investments. This can make Europe attractive for international AI investments.

American criticism and European response

The US criticizes Europe's approach as over-regulated and innovation-hostile. American tech lobbies warn that Apply AI is "too little, too late" compared to the hundreds of billions the US and China invest.

The European response emphasizes quality over quantity: Europe focuses on trustworthy AI and specific use cases, not on racing to the largest models. This is a deliberate strategic choice. Additionally, Europe points to the sustainable advantage: European data protection standards are becoming the global norm, and companies building on this gain a long-term competitive advantage. Finally, the crucial point is that the €1 billion is seed capital to mobilize much more private investment - the goal is to unlock €10+ billion in private investments.

Practical roadmap for organizations: how to benefit now

If your organization wants to benefit from Apply AI, follow these steps:

Phase 1: Orientation and positioning (now - December 2025)

Phase 2: Application and partnership (January - June 2026)

The first Horizon Europe call opens in December 2025, but consortium building starts now. Successful applications usually have 6-9 months of preparation time.

From March 2026, organizations can request free access to AI testing environments through Digital Europe Testing Facilities. This is ideal for companies wanting to experiment without large investments.

Check with your national innovation agency when Apply AI co-funding opens. Often preparatory grants are available for consortium formation.

Phase 3: Execution and scaling (2026-2028)

Successful projects move from proof-of-concept to pilot to commercial scaling. Use milestone-based funding to spread risk: start small, prove value, then scale up.

The regulatory and financial landscape evolves rapidly. Stay informed through updates from the EU AI Office, your national AI coalition, and relevant industry associations and networks where you're actively involved.

Case study: how an SME can leverage Apply AI

This case is fictional but realistic, based on actual Apply AI opportunities

AgriSense BV is a European scale-up with 45 employees providing sensors and software for precision agriculture. They have a working product for soil moisture monitoring but want to use AI to automate advisory services.

The challenge

AgriSense is in a classic scale-up situation. The company has collected extensive data - millions of measurements from thousands of sensors - but lacks the expertise to leverage it optimally. Customers increasingly ask for automated irrigation advice, but in-house AI expertise is limited. Moreover, the budget for large-scale AI development is lacking, making external financing necessary.

Apply AI strategy

Step 1 (Q4 2025): AgriSense contacts a university for a Horizon Europe consortium. The university has AI expertise and field-test facilities. They also seek a Spanish partner (agri-tech in Andalusia) and a Polish sensor manufacturer.

Step 2 (Q1 2026): The consortium submits a Horizon Europe application (€2.4 million over 3 years). AgriSense commits €180K own funds + 12 months FTE from their CTO.

Step 3 (Q2 2026): The application is approved. AgriSense gains access to university AI expertise and high-performance computing, essential for training complex models. Via the Digital Europe Testing Facility, they can safely experiment with different model architectures. Additionally, the Spanish and Polish test locations enable system validation in different climates, making the model more robust.

Step 4 (2026-2027): The team develops an AI model that predicts irrigation needs based on sensor data combined with weather forecasts. The system advises not only whether to irrigate but also on optimal timing and water quantity. Crucially, the model continuously learns from historical data and results, making advice increasingly accurate.

Step 5 (2028): The product launches commercially. AgriSense now has an AI-powered irrigation advisor delivering 20-30% water savings. The company grows to 120 employees with clients in 12 EU countries.

What made this successful?

AgriSense's success can be traced to five critical factors. First, there was a clear use case with demonstrable customer need - not a solution looking for a problem. Second, complementary partners were selected, each bringing essential expertise: the university for AI knowledge, the Spanish partner for Mediterranean context, and the Polish manufacturer for hardware integration. Third, a realistic scope was maintained: not "AI for all agri-problems" but solving one specific problem well. Fourth, the commercial path was clear from day one - how this becomes a product customers want to buy. Finally, the European dimension with multinational test sites created a more robust model that works in various conditions.

Future perspective: what comes after Apply AI?

The Apply AI initiative runs until 2028. What next? The Commission has signaled this is the first tranche of a multi-year AI investment program.

Apply AI 2.0 (expected 2028-2032)

Depending on the first phase's success, an Apply AI 2.0 is expected with significantly larger budget, possibly €3-5 billion if the current phase meets its goals. The scope would broaden, expanding to sectors like education, culture, and justice currently outside the program. Crucially, the focus shifts from pilots to deeper integration, with AI structurally implemented in the European economy rather than remaining experimental.

Integration with other EU programs

Apply AI is part of a broader European ecosystem of technology investments. The European Chips Act invests €43 billion in semiconductor capacity, essential for the hardware running AI. The European Cloud Initiative builds European cloud infrastructure for sensitive workloads, ensuring Europe doesn't remain fully dependent on American cloud providers. Horizon Europe represents €95.5 billion total for R&D, a substantial part AI-related. These programs reinforce each other in a coherent stack: chips for AI hardware, cloud for AI infrastructure, Apply AI for actual applications.

The long-term vision: Europe as global AI leader in specific domains

Europe cannot compete with the US and China in all AI domains. The strategy is selective excellence:

Conclusion: a new chapter in European AI ambition

The Apply AI initiative marks a fundamental shift in Europe's AI strategy. After years of focus on regulation, Europe now chooses a balanced approach: strict rules for safety and ethics, combined with substantial investments in innovation and adoption.

Three core messages for organizations:

The first message is that this is not symbolic policy: €1 billion is substantial, and through co-funding and private matching, this can mobilize €10+ billion in AI investments in the coming years. This is real money for real projects.

Secondly, the opportunities are real but require action: Passive waiting doesn't work. Successful organizations are already starting with networking, building consortia, and developing use cases. The preparation time for successful applications is at least 6-9 months.

Thirdly, European compliance becomes a competitive advantage: Companies investing in AI Act-compliant systems position themselves not only for the European market but for global adoption, as other regions adopt similar standards.

The next 6-12 months are crucial. Application rounds open, consortia are formed, first projects start. Organizations taking position now can benefit from first-mover advantages and help shape Europe's AI future.

The question is no longer whether Europe invests in AI, but how effectively we convert these investments into economic growth, societal impact, and strategic autonomy.

Official sources and further information:

• European Commission: Apply AI Initiative
• Horizon Europe: AI Partnership
• Digital Europe Programme
• European Investment Bank: AI Financing

Want to know how your organization can benefit from Apply AI funding while remaining compliant with the EU AI Act? Contact us for a no-obligation conversation about the possibilities.