The wealth management sector is an important pillar of Singapore’s financial services industry and is characterized by high performance expectations, strong client orientation, and increasing technological transformation. Traditional Job Demands–Resources (JD-R) research typically links job demands with negative work outcomes. This study, however, challenges this assumption within the context of wealth management professionals.

Drawing on the JD-R framework, we propose and test an integrative moderated mediation model examining how job demands and job resources influence work engagement through job-based psychological ownership (JBPO), while incorporating AI perceptions as contextual moderators. Specifically, we examine AI anxiety and AI augmentation to understand how employees’ interpretations of AI reshape work experiences.

By collecting data from 201 employees in Singapore's wealth management sector using a two-wave dataset, our findings contradict conventional JD-R assumptions and show that both job demands and job resources positively predict work engagement through JBPO. Even under conditions of high AI anxiety or AI augmentation perceptions, the indirect effects remain mostly positive.

The findings suggest that wealth management professionals may interpret demanding work conditions as opportunities for competence and ownership rather than as stressors. In addition, the findings also provide actionable insights for financial organizations to leverage both AI and challenging job designs to bolster employee well-being and productivity.

Authors:
Jieqiong Cao, Singapore University of Social Sciences, Singapore
Derek Tay, Kamet Capital Partners Pte Ltd, Singapore

About the Presenter(s)
Dr Jieqiong Cao is a University Assistant Professor/Lecturer at Singapore University of Social Sciences in Singapore

See this presentation on the full schedule – Tuesday Schedule

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