Artificial intelligence (AI) technologies are fundamentally changing the nature of work. Specifically, AI algorithms are challenging the humans in knowledge work. Therefore, while enjoying the benefits of AI, many organisations face difficulties managing knowledge work performed together by humans and machines. To date, there is a lack of empirical research on how organisations manage the transformation of knowledge work when adopting AI technologies. With the aim of delving into this emerging phenomenon, we conducted an in-depth case study at the Finnish government shared services centre during their implementation of an AI-centric robotic process automation (RPA) technology. To theorise how humans and machines work together, we adopted a theory of knowledge embodiment. Based on our initial qualitative interpretive analysis of the case data, we identified four cognitive stages: cognitive reasoning, cognitive collaborating, cognitive scaffolding, and cognitive extending. Moving forward, we deepen our under-standing of how these stages form a process of knowledge embodiment. Our research aims to contribute to theory by conceptualising the knowledge embodying process in the future of work, meantime extending the theory of knowledge embodiment. We contribute to practice by providing implications on how humans and machines perform knowledge work together in organisations where AI technologies are used.
Dias, Malshika; Pan, Shan; and Tim, Yenni, (2019). "KNOWLEDGE EMBODIMENT OF HUMAN AND MACHINE INTERACTIONS: ROBOTIC-PROCESS-AUTOMATION AT THE FINLAND GOVERNMENT". In Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019. ISBN 978-1-7336325-0-8 Research-in-Progress Papers.