Background

European cities and regions are increasingly integrating AI to improve internal efficiency (e.g., internal AI agents), deliver public services (AI-driven citizen-oriented services), and urban planning (traffic management, environmental monitoring, citizen engagement). At the same time, reliance on Big Tech digital infrastructure is creating concerns about technological dependence, data protection, ethical governance and alignment with European values.

Governments face a growing disconnect between rising expectations for speed, adaptability and responsiveness, and institutional systems that have not kept pace. Digital technologies are now essential for addressing today's policy and service delivery challenges.

While the OECD data shows progress in digital strategies and frameworks, the focus must shift to delivering real impact through stronger data governance, wider use of digital infrastructure, modernised investment, trusted AI, and more human-centred services.

The EDIH Summit 2026 brings together the full European Digital Innovation Hubs (EDIH) network, EU institutions, Member States, AI infrastructures and innovation actors to examine how Europe’s AI ecosystem functions in practice. Sessions will explore how EDIHs connect organisations with other actors of the EU AI innovation ecosystem such as AI Factories, Testing and Experimentation Facilities (TEFs) and regulatory sandboxes; how common tools and assessment frameworks support this work; and how proven approaches can be scaled across regions and sectors.

The Open Source Observatory (OSOR) is organising a workshop dedicated to exploring the role of open source AI in the public sector. 

How do citizens perceive the use of AI in government? While AI has the potential to improve efficiency and service quality, it may also influence public trust—either strengthening it through better performance or undermining it if it is perceived as unfair or inappropriate. How these systems should be designed and deployed in ways that align with citizens’ expectations, feelings, and needs remains an open question. Emerging evidence is beginning to shed light on these dynamics, yet the topic remains under-discussed in current policy debates. 

Generative AI is rapidly reshaping government operations, with public employees increasingly relying on commercial tools - often in informal or “shadow” modes that are difficult to monitor and govern. At the same time, administrations are beginning to experiment with governance approaches, including secure-by-design environments, guidelines, and training initiatives, although these efforts remain fragmented. Tensions between innovation, control, and safety are emerging, and the optimal balance between these dimensions is still to be defined.