Adoption of Artificial Intelligence Technologies in Production: Empirical Insights from the Manufacturing Industry

Artificial intelligence (AI) has developed rapidly in recent years and is now used in many areas of life. Despite promising fields of application and potential for increasing efficiency in manu-facturing, the implementation of AI, especially in production, remains cautious. This disserta-tion aims to shed light on the challenges and prospects of AI adoption in production by exam-ining various factors, influences, and effects on resilience and product innovation. The investi-gation consists of four scientific journal articles and is supplemented by empirical findings from a systematic literature review (SLR) and quantitative analyses from the German Manufacturing Survey (GMS). This data basis allows for a comprehensive examination of AI adoption in pro-duction from different perspectives.
The first article analyzes the current state of research on the adoption of AI in production based on a systematic analysis of the literature. This analysis identifies influencing factors that are important and serve as a basis for subsequent studies. The second article examines the influence of AI readiness on AI adoption in production, taking into account various dimensions of readi-ness (technological, organizational, and their combination). The results show that organiza-tional, and especially combined AI readiness, have a significant positive influence on the prob-ability of AI adoption, underscoring the particular importance of organizational resources in the implementation of AI solutions in production. The third article explores the influence of AI readiness on the resilience of production systems. The analysis reveals that companies with higher AI readiness are better able to respond to disruptions, such as those that occurred during the COVID-19 pandemic, and recover more quickly. These results highlight the strategic rele-vance of AI for stability and adaptability in production. In the fourth article, the focus lies on analyzing the influence of AI adoption in production on product innovations. It considers dif-ferent types of product innovations: new for the company, new to the market, digital-oriented as well as eco-oriented. The analyses show that AI adoption has a positive influence on different types of product innovation, especially digital product innovations.