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AI Experience Lab


Added by:   OECD analyst
Added on:   16 Jul 2026
Updated by:   OECD analyst
Updated on:   17 Jul 2026

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The AI Experience Lab is a capacity-building initiative of the National Institute of Administration where public organisations can safely experiment with AI for real public service needs. It follows three phases — ideation, training and deployment — combining a 90-hour certified training programme with hands-on experimentation, in collaboration with leading national universities and major technology consulting firms. Participants finish the Lab with a PoC, functional prototype or MVP.

Initiative overview

The AI Experience Lab was created to address a growing gap in the public sector between the potential of artificial intelligence and the actual capacity of public organisations to use it safely, effectively and responsibly. Many public bodies face limited technical skills, fragmented data and uncertainty about risks, which makes it difficult to move from interest in AI to informed decision-making. The Lab responds to this challenge by offering a protected environment where public organisations can explore AI through real use cases without immediate pressure to procure or deploy solutions.

The main objective of the AI Experience Lab is to build lasting capacity in public administration. It supports organisations through a structured journey that combines ideation, certified training and practical application, enabling participants to better understand AI, its limitations and its value for public services. A key goal is to ensure that public entities are able to make informed choices about if, when and how AI should be used, while reinforcing trust, responsibility and alignment with public values.

To date, the Lab has supported the development of 10 AI projects across different public sector domains, including employment services, financial inspection, public management, regional administration and public sector training. These use cases address concrete challenges such as improving service delivery, supporting decision-making, reducing administrative burden, strengthening risk analysis and improving planning. Each project is developed in collaboration with leading national universities in technology, business and management, and major technology consulting firms, ensuring both scientific rigor and practical relevance.

Looking ahead, the AI Experience Lab is expected to evolve as a permanent capacity-building framework within the National Institute of Administration. Its results — certified skills, tested solutions and practical knowledge — create a foundation for scaling successful approaches across the public sector. Over time, the Lab aims to strengthen a community of practice (CoP), support the institutionalisation of AI capabilities in public organisations and contribute to a more capable, autonomous and future-ready public administration.

Other relevant details

Results, outcomes and impacts: So far, the AI Experience Lab has supported the development of 10 AI projects across public sector organisations, each delivering a PoC, functional prototype or MVP, alongside a 90-hour certified training programme. As the initiative has been operating for only six months, some projects are still ongoing and longer-term impacts are still being assessed. Initial results include increased skills, organisational readiness and more informed decision-making. Results have been measured through concrete project deliverables, milestone-based reviews and participant feedback. To assess longer-term impact, a follow-up questionnaire is applied one year after participation to determine whether projects continued, were scaled, procured or transferred. Challenges and lessons learned: A joint assessment after the first six months of the AI Experience Lab identified key structural challenges to public sector AI adoption, including weak data governance, licensing and sovereignty concerns, rigid procurement processes and skills gaps, which limit the scale and speed of experimentation. In response, the Lab was designed as a safe learning environment and introduced a dedicated data governance module alongside training on AI fundamentals, ethics, change management, agile project management and smart financing. A key lesson is that successful AI adoption goes beyond technical solutions, requiring skills, governance, legal clarity, organisational readiness and strong alignment between leadership, capacity-building, data strategy and procurement.