Abstract
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Driven by experiences from the private sector, public institutions have also started adopting various artificial intelligence (AI) technologies in numerous subsectors, e.g. healthcare, law enforcement, defence, public finance (taxation), education, social services, transport, and infrastructure engineering. Adopting new technologies requires the transformation of the organisation in both hard (structure, processes, etc.) and soft aspects (people, organisational culture etc.). Namely, the barriers to the new technologies’ adoption are usually not the technologies themselves but the enablers influencing AI adoption, such as the organisational, technological infrastructure, individual aspects etc. To exploit the full potential of AI in the public sector, the main objective of the ongoing study, presented in a paper, is to systematically analyse state-of-the-art in the field of AI adoption in public institutions and related organisational changes, in this case with a specific focus on barriers to AI adoption. The purpose of the ongoing study is to design a set of recommendations for decision-makers (policymakers and public managers) as well as for public employees when implementing the processes of AI adoption - to be as effective and efficient as possible. The study was designed as a systematic literature review using the PRISMA protocol. The preliminary results show that previous studies on AI adoption in public institutions detected many barriers to AI adoption related to the organisational elements, such as people/employees, structure, culture, technology, and processes. It is crucial for decision-makers and implementers of AI to understand the possible barriers listed in the paper, which can be used as guidelines for successful preparation for AI adoption at all public institutions’ levels.
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