How can Ai implementation within asset management be successfully organized?
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2023-08-31
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en
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The aim of this study is to investigate how to successfully organize AI implementation in asset management. To date, there has been a lack of research in this area, with previous studies primarily focusing on technological advancements and neglecting organizational aspects. To gather insights, an inductive approach was taken, involving interviews with ten experts experienced in AI implementation within the infrastructure industry. The findings highlight the importance of end users in AI implementation, as they are the ones who utilize the AI tools and verify data. Successful AI implementation requires organizational adaptation, including an innovation vision, employee composition, and strategy. The fragmented nature of asset management underscores the need for strategic flexibility. Team management, particularly diverse teams incorporating domain knowledge, enhances AI implementation. Effective data management, including long-term and comprehensive data collection, is vital for accurate asset management, necessitating a shift in focus towards data acquisition. It emphasizes the role of domain expertise in team management for proper understanding and utilization of data through feedback. Also, the essence of early implementation to gather feedback, ensuring data accuracy and reliability. It also highlights the need for strategic flexibility to address the current fragmented asset structure in asset management.
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Faculteit der Managementwetenschappen