Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies

• Published in: Technovation 2022-02, Vol.110, p.102375, Article 102375
• Main Authors: Kinkel, Steffen, Baumgartner, Marco, Cherubini, Enrica
• Format: Article
• Language: English
• Subjects: Artificial intelligence (AI); Digital skills; Industry 4.0; Machine learning (ML); Technology adoption; Technology-organization-environment framework
• ISSN: 0166-4972; 1879-2383
• DOI: 10.1016/j.technovation.2021.102375

In current discussions, Artificial Intelligence (AI) is ascribed great influence on production processes. Research on AI has seen tremendous growth in recent years. However, most of the research has focused primarily on various AI technologies, and less on prerequisites and enablers for adoption of AI at firm-level. This is surprising, given the fact that many companies are still struggling to establish AI in their production and to drive their AI adoption forward. To close this gap, this study analyses the impact of various technological, organizational and environmental (TOE) prerequisites for a successful adoption of AI technologies in manufacturing. Based on a cross-national survey of 655 company representatives from the manufacturing industry, our results contribute to a better understanding of why some companies are more determined than others when it comes to implementing AI in their production. We find evidence that organizational factors, such as digital skills, company size, and R&D intensity, have the greatest impact on the adoption of AI in manufacturing. Furthermore, in order to gain new insights into the interplay of new technology adoption and global production strategies, this paper addresses the question of which factors explain a primarily domestic or globally oriented technology adoption. We find that especially research-intensive, knowledge-based and service-oriented companies tend to roll out AI technologies not only at their domestic but also at their foreign production sites. •Transnational survey on the current adoption status of AI in the manufacturing industry.•Validation of company characteristics as prerequisites for adopting AI.•Examination of digital skills as the key enabler for AI adoption.•First insights into which companies roll out AI technologies globally or only domestically.