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From automats to algorithms: the automation of services using artificial intelligence

Chris Meyer (Rensselaer Polytechnic Institute, Troy, New York, USA)
David Cohen (Skidmore College, Saratoga Springs, New York, USA)
Sudhir Nair (University of Victoria, Victoria, Canada)

Journal of Service Management

ISSN: 1757-5818

Article publication date: 31 March 2020

Issue publication date: 24 September 2020




The paper aims to fill this gap by positing a framework that considers the service automation decision as a matter of knowledge management: a choice between human resident and codified knowledge assets.


The paper is a conceptual paper, grounded in the knowledge-based view.


The paper uses the information processing theory, which argues that the level of uncertainty in a process should dictate the type of knowledge deployed, as the contingency for the automation choice, and customer interaction uncertainty as the driver of that contingency. From these ideas, propositions are generated relating customer interaction uncertainty and service automation. Further implications for artificial intelligence (AI) are also explored.


The framework illuminates and informs the strategic choices regarding service automation, including the use of AI in professional services, a timely and highly important topic. It offers a valuable model for practitioners and contributes to the academic literature by pointing the way for future directions for scholarly research.



Meyer, C., Cohen, D. and Nair, S. (2020), "From automats to algorithms: the automation of services using artificial intelligence", Journal of Service Management, Vol. 31 No. 2, pp. 145-161.



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Copyright © 2020, Emerald Publishing Limited

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