Impact of Artificial Intelligence on Management and Leadership in Research & Development : A Case Study of Thermo Fisher Scientific

Abstract: Background: In current business world, big data and Artificial Intelligence (AI) implementation in daily business has become a mega-trend in different organization functions across various industries. The questions of what impacts against management and leadership can be expected with AI application, and how to make the most of AI application to achieve innovation success have become extremely interesting for business leaders, especially in R&D department which is considered to be innovation locomotive of a company. Objectives: Existing studies on implementation of AI application in research and development (R&D) department is rather scarce although there is a strong relevance for AI to be brought into R&D for achieving successful innovation. This study tries to fill this gap in literature aiming to explore the impacts of AI application on management and leadership, and also how AI can be used for achieving innovation success in R&D department. Method: The research methodology chosen for this study is a single and holistic case study on the organisation Thermo Fisher Scientific as we considered our research question to be unexplored and rare. We have used multiple sources of data including both primary data from multiple interviews and secondary data in the form of publicly available data. For the analysis of the data, we have used the grounded theory approach with 9 interviews for a phenomenological study. Results: A theoretical dynamic model was created for explaining the mechanism of AI influences in R&D by using grounded theory based on empirical interview data analysis. Interesting findings shed light on importance of implementation of AI application in R&D. The results disclose that AI application in R&D can lead to higher efficiencies in processes, decision making, costs and stimulate innovation, while a shift of leadership elements and organizational structure changes can be expected.