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.
Abstract
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.