Working paper

Artificial intelligence adoption in the public sector: a case study

This case study illustrates the drivers of and barriers to AI adoption by organisations, and acceptance of AI by workers in the public sector.

Publishing date
16 March 2023
Laura Nurski
An Artificial Intelligence camera


This case study illustrates the drivers of and barriers to artificial intelligence adoption by organisations, and acceptance of AI by workers in the public sector. Several factors were crucial in the successful adoption of a human-centred approach to AI, including a fast discovery phase that involved workers (or end users) in the development early on, and aligning human resources, information technology and business processes. Subsidy support mechanisms were also specifically targeted and acquired to support the adoption.

However, making AI support available to workers proved insufficient to ensure its widespread usage throughout the organisation. The slow adaptation of existing work processes and legacy IT systems was a barrier to the optimal usage of the technology. Moreover, the usefulness of the technology depended on both the task routineness and worker experience, thereby necessitating a rethinking of the work division between technology and workers, and between junior and senior workers. 

Successful human-centred roll-out of AI in Europe will therefore depend on the availability of, or investments in, complementary intangible organisational capital. Very little is currently known about these investments.

The author is grateful to Tom Schraepen (Bruegel) for research assistance, to Mia Hoffmann (Georgetown’s Center for Security and Emerging Technology) for comments on earlier versions, and to the contacts at the case organisations, who provided their cooperation and input to the study.

This was produced within the project "Future of Work and Inclusive Growth in Europe" with the financial support of the Mastercard Center for Inclusive Growth.

About the authors

  • Laura Nurski

    Laura Nurski was a non-resident fellow at Bruegel until 2024. She is a Research Expert at the Centre of Expertise for Labour Market Monitoring at the Faculty of Business and Economics of KU Leuven. She leads the development of an integrated labour market prediction model that identifies future skill needs in the Flemish labour market.

    While residing at Bruegel in the past, she led the Future of Work and Inclusive Growth project which analyses the impact of technology on the nature, quantity and quality of work, welfare systems and inclusive growth.

    Before joining Bruegel, she investigated the impact of job design and organisation design on wellbeing and productivity at work. This inherently multidisciplinary domain has left her with a broad social science background, encompassing psychology, sociology and economics. As a former data scientist in the financial and retail sector, Laura is passionate about data and technology. She is also a skilled statistical programmer, survey developer and open-source aficionado.

    Laura holds a Ph.D. in Industrial Organization, a M.Sc. in Economics and a M.A. in Business Engineering from KU Leuven.

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