Acceptance of AI in the workplace: Literature analysis and process-oriented methods to foster organizational acceptance and trust of AI

Abstract

The use of artificial intelligence (AI) in manufacturing can increase productivity, improve decision-making, reduce routine tasks, and enhance both workplace safety and job satisfaction. However, our studies indicate that employees without managerial roles often express reservations toward AI, while managers identify acceptance as a major obstacle. The aim of this paper is therefore to identify interventions that foster acceptance of AI in manufacturing. A systematic literature review was conducted following the PRISMA approach. Out of 295 initially identified publications, nine were analysed in detail using qualitative content analysis based on Mayring. This process yielded twelve categories with a total of 44 interventions, which were mapped onto a process-oriented model for fostering acceptance and trust. The interventions focus strongly on the early stages of implementation and emphasize qualification, demonstration of added value, participation, internal communication, cooperation, and corporate culture. While technical characteristics of AI systems remain relevant, they are outweighed by human and organizational factors. The findings suggest that companies should not rely solely on technical solutions but must also invest in employees, communication, and culture to secure sustainable acceptance.

Keywords: Artificial Intelligence, Manufacturing, Technology Acceptance, Organizational Interventions

DOI: 10.54941/ahfe1006926