How manufacturing leaders shape employee attitude towards AI adoption: A retrospective analysis from change management literature

Artificial Intelligence (AI) constitutes the most recent advancement in Digital Transformation (DT), with growing prevalence across societal domains. Within the field of business, its unparalleled capabilities and implications are becoming more evident at a rapid pace. This development has generated employee concerns regarding job security and their ability to remain competitive in an AI-integrated workplace. This shift in ‘employee attitude’ has been proven to produce negative outcomes for organizations and people alike, though research indicates that employee attitudes toward technological change are malleable through targeted intervention. Organizational leaders have been shown to hold a certain influence over their subordinates’ cognitive and behavioral reactions in such periods of fundamental change. This research performs an analysis by meticulously following a systematic literature review (SLR) process, carefully selecting and analyzing twenty articles. By using a coding method, a well-documented shortcoming of the highly relevant Technology Acceptance Model (TAM) was identified. Leveraging yet another theory on employee attitude, Solberg’s digital mindsets, and combining the two theories in a single model, led to a novel contribution to existing literature. By incorporating an additional leadership dimension, this study develops a four-quadrant framework aimed at proposing fitting leadership approaches for particular employee digital mindsets in face of technological change.