Even though artificial intelligence (AI) has great potential in several sectors, AI adoption in healthcare remains a difficult topic facing several challenges. In addition to the difficulties posed by the technology itself, there are challenges in the social sphere, involving both structural and individual components. Some nations are at the forefront of implementing AI in healthcare compared to others. To date, little AI research considers socio-technical dimensions to explain differences in healthcare AI adoption between countries. We address this research gap by identifying and analyzing challenges by applying the socio-technical theory (STT) with a focus on Germany and China. Some adoption challenges occur independently of national context, whereas others must be considered in the context of country characteristics. In addition, we discuss reasons for the varying adoption rates between Germany and China, include national culture dimensions and suggest propositions for national healthcare AI implementation strategies.
Kus, Kevin; Arlinghaus, Tim; and Teuteberg, Frank, "Analyzing Healthcare AI Adoption in China and Germany through the Lens of Socio-Technical Theory: A Literature Analysis" (2022). PACIS 2022 Proceedings. 126.
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