Abstract
Research on information systems (IS) has identified diverse problems encountered in system implementation and organizational change. We reviewed and analyzed the implementation problems explored in prior research to determine the core problems and the important causal relations between the problems. The causal mechanism behind the relations was articulated with illustrating examples. This analytical review provides a deeper understanding of the fundamental aspects of IS implementation processes, which are conducive to preparing for the implementation of artificial intelligence (AI) systems. AI systems are an information system as well. However, by embedding machine learning elements and necessary data flows, the implementation of AI systems would be much more complicated and challenging. We derived useful implications for AI systems implementation by advancing the understanding of the core problems of IS implementation and connecting them with the fundamental problems inherent in AI systems. The analyses and discussions motivate further studies on implementing IS with or without AI.
Published Version
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