CEPS Task Force Targets EU Apply AI Strategy Implementation
The European Commission's Apply AI Strategy, launched in October 2025, represents a policy pivot from regulation to deployment. The Centre for European Policy Studies (CEPS) is launching a dedicated Task Force to bridge the gap between the Strategy's ambitions and practical execution.
This initiative responds to a critical reality: the Strategy carries no dedicated budget, unresolved questions about infrastructure, and a history of EU data-sharing initiatives that have struggled to deliver. CEPS Director of Research Andrea Renda has flagged these implementation challenges in recent analysis.
The Task Force operates as a structured research and engagement platform. It brings together senior executives, policymakers, industry experts, and researchers to work through the hard questions the Strategy raises. Outputs will feed into the Apply AI Alliance process.
Three sector tracks define the work:
- Track 1 Healthcare & Pharma: AI-assisted diagnostics, drug discovery, precision medicine, the European Health Data Space, and regulatory pathways under the AI Act and Medical Devices Regulation
- Track 2 Automotive, Mobility & Transport: Software-defined vehicles, autonomous driving, agentic AI for manufacturing and supply chains, connected vehicle data ecosystems, and harmonised type-approval frameworks
- Track 3 Government & Public Sector: Workflow automation, citizen-facing AI services, public procurement of AI, sovereign AI infrastructure, and AI Act compliance for high-risk public sector applications
Each track applies a consistent five-pillar analytical framework. The framework covers key use cases, infrastructure requirements, data governance, flagship applications, and sovereignty and implementation roadmaps. All three tracks engage with the shared EU policy environment, including the AI Act, the Data Strategy and Data Act, the Cloud and AI Development Act, AI Factories and Gigafactories, and the Competitiveness Compass agenda.
The timeline is tight. The Task Force runs from June 2026 to February 2027. Nine hybrid working sessions will run June through December 2026, followed by a drafting and member review phase. A final report launches in February 2027. Each session produces a detailed written overview circulated to all participants.
Registration closes 31 May 2026. Organisations may join one, two, or all three tracks. They may register up to two representatives who can rotate across sessions. An information session for prospective participants takes place 15 April 2026. Full details, including the participation fee structure, appear in the prospectus on the CEPS Task Force webpage.
CEPS's role is that of organiser, convener, and analytical lead. The Task Force team, led by Renda and including CEPS researchers and external advisors across all three tracks, conducts all research. They produce all briefings and session materials. They synthesise outputs into the Final Report and sector policy briefs.
Participating organisations engage in the analytical process. They contribute their expertise to structured discussions. They are credited as co-authors in the final deliverables. Member contributions are invited and welcomed but do not determine the Task Force's conclusions. The Task Force operates under CEPS integrity standards. Chatham House Rules apply throughout.
The Apply AI Strategy builds on the Draghi Report's call for renewed industrial competitiveness. It also follows the Competitiveness Compass's vision for a "CERN for AI." The Strategy sets out to scale AI deployment across eleven strategic sectors. It adopts an ecosystem approach, connecting use cases with infrastructure, data governance and skills needs.
It avoids one-size-fits-all solutions in favour of tailored, sector-specific flagships. It keeps a firm link with the broader EU legislative agenda. It anchors investment in a common, open-source pan-European frontier AI model. But the Strategy comes with significant implementation challenges (a problem that has plagued EU tech policy for years, frankly).
Independent reporting from Thrumos corroborates the scope and timeline of the initiative. The outlet notes the Task Force addresses five issue areas per sector and will produce a Final Report with cross-sectoral analysis and recommendations.
Deliverables include three sector policy briefs covering Healthcare, Automotive, and Government. The Task Force also aims to establish a stakeholder network connecting EDIHs, industry, and policymakers. This network could prove valuable for organisations operating in EU markets or watching European AI governance as a leading indicator.
The physical reality of participation matters. Sessions are hybrid, with physical attendance strongly encouraged. Participants will sit through working sessions, review written overviews, and engage in structured discussions. They'll navigate the friction of coordinating across sectors, time zones, and organisational priorities.
Whether the Task Force's recommendations actually move the needle remains the real question. The EU has a track record of producing policy documents that gather dust. The Apply AI Strategy's success depends on whether industry, researchers, and policymakers can align on what implementation actually looks like across each sector. Time will tell if this structured approach changes that dynamic.
Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn
Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt
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