The evolution of artificial intelligence adoption in industry

Abstract

Artificial intelligence (AI) in the fourth industrial revolution is a key building block and is becoming more significant as digitization increases.AI implementation in enterprises is increasingly focused on the technological and economic aspects, disregarding the human factors. In this context, the implementation and success of AI technologies depend on employee acceptance. Low employee adoption can lead to poorer performance as well as dissatisfaction. To ensure the expected added value through AI, it is necessary for companies to increase AI acceptance. People see AI as a machine with human intelligence that surpasses employees' capabilities and acts autonomously. Moreover, workers therefore fear that AI will replace humans and that they will lose their jobs in this way. This aspect leads to a distrust of the new technology. This results in a negative attitude towards AI. Since the research field of AI acceptance and its influencing factors have not been sufficiently investigated so far, the aim of this study is to analyze the development of AI acceptance in the industrial environment.In order to achieve the goal of this study, the systematic literature review according to Tranfield et al. (2003) is chosen as the research method, as it draws on previous results and in this way the development of acceptance can be investigated. After discussing the relevance of the topic and the resulting problem, an explanation of the terms that are considered important for the understanding of this study follows. Thereupon the systematic literature research is planned, in which different search terms and databases are determined.In order to analyze the development of the individual aspects, these were then compared with the factors from existing technology acceptance models from earlier years. This provides the insight that the workers without AI experience tend to reject the AI technologies due to the fear of consequences and other factors, therefore, an increase in AI understanding through improved expertise is required. In addition, this work shows that insufficient infrastructure in enterprises slows down AI adoption, which is one of the main problems. Based on the results, a model is established for this purpose, which is compared with the technology acceptance models and the Unified Theory of Acceptance and Use of Technology model to show the similarities and differences of the factors of technology acceptance.