Artificial intelligence and smart workplace practices in healthcare: Driving knowledge sharing, green learning, and employee voice.

Authors

Amir A Abdulmuhsin, Mohammed Saud Abdulrazzaq, Abeer F Alkhwaldi, Mohd Abass Bhat, Shagufta Tariq Khan, Saad G Yaseen

Published in

Work (Reading, Mass.). Pages 10519815261492329. Sep 30, 2026. Epub Sep 30, 2026.

Abstract

BackgroundKnowledge sharing and digitally enabled workplace practices can promote environmentally sustainable behaviour in healthcare organisations. However, limited research has examined how smart workplace practices transmit the effects of knowledge sharing on green learning and green employee voice.ObjectiveThis study investigates the effects of knowledge sharing on green learning and green employee voice and examines the mediating role of artificial intelligence enabled workplace practices in these relationships.MethodsA positivist, quantitative design was adopted. Data were collected from 1954 professionals employed in private hospitals in emerging country and analysed using Partial Least Squares Structural Equation Modelling and Necessary Condition Analysis.ResultsKnowledge sharing had significant positive effects on green learning (β = 0.469, p < 0.001), green employee voice (β = 0.455, p < 0.001), and smart workplace practices (β = 0.594, p < 0.001). Smart workplace practices partially mediated the effects of knowledge sharing on green learning (indirect β = 0.249, p < 0.001) and green employee voice (indirect β = 0.271, p < 0.001). The model explained 62.9% of the variance in green learning and 66.2% in green employee voice. Necessary Condition Analysis also identified knowledge sharing as a necessary condition for achieving these green outcomes.ConclusionsKnowledge sharing facilitates green learning and employee voice both directly and through smart workplace practices. Healthcare managers should integrate knowledge-sharing mechanisms with smart workplace systems to cultivate environmentally responsible learning and communication behaviours.

PMID:
42813802
Bibliographic data and abstract were imported from PubMed on 30 Sep 2026.

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