From automats to algorithms: the automation of services using artificial intelligence
Chris Meyer, David Cohen, Sudhir Nair
Abstract
Purpose 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. Design/methodology/approach The paper is a conceptual paper, grounded in the knowledge-based view. Findings 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. Originality/value 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.