Leveraging AI for Service Productivity in Heavy-Duty Truck Repair and Maintenance Operations : A Case Study on AI Usage and AI Adoption Challenges

Sammanfattning

Artificial intelligence (AI) has attracted significant attention within academia and among businesses following technological advances over the last decade. The technology is transforming the way businesses create and deliver value to their customers. Yet there is still a lack of research regarding how AI creates value for businesses and what challenges businesses face on their journey towards AI adoption. This study sets out to explore the usage of AI within heavy-duty truck repair and maintenance operations at Scania, a leading manufacturer of heavy-duty trucks.Interviews were conducted with key stakeholders to examine three AI use cases: (1) predictive maintenance, (2) symptom analysis, and (3) service coordination automationin terms of service productivity gains and AI adoption challenges. The research on AI adoption challenges extends beyond the three cases to include general AI adoption challenges, based on interviews at Scania and complementary findings from three additional industrial companies. The findings demonstrate how AI can significantly increase service productivity through improvements in internal efficiency, external efficiency, and capacity efficiency. Moreover, AI adoption is found to be inhibited by both technological and organizational challenges that must be addressed to succeed with the technology. Contributions to academic literature are made by delineating the role of AI for service productivity withinheavy-duty truck repair and maintenance operations. In addition, the study provides empirical support for existing theories on AI challenges through detailed practical insights in an industrial setting. Future research should aim to quantify the benefits of AI adoption and its effect on service productivity, as well as explore how different organizational characteristics influence AI adoption challenges.