Artificial Intelligence, Psychological Well-being and Workforce Productivity in Higher Education: An Educational Psychology Perspective on Sustainable Human Capital Development.

Abstract

Artificial Intelligence (AI) is reshaping teaching, research and administration in universities, yet its psychological consequences for academic staff are under-examined. This paper proposes and specifies a mixed-methods study of how AI competence and perceived organizational support relate to work engagement, psychological well-being and workforce productivity among lecturers and academic support staff in selected African universities. Grounded in the Job Demands–Resources (JD-R) model and Self-Determination Theory (SDT), the study treats AI as both a job resource (automation, feedback, time savings) and a job demand (learning load, technostress, fear of displacement). An explanatory sequential design is proposed: a cross-sectional survey of about 400 staff using validated scales, analysed with descriptive statistics and structural equation modelling (SEM), followed by 20–24 semi-structured interviews analysed thematically. Because data collection is still to be completed, the Results section reports the pre-specified hypotheses, fit criteria and the pattern of findings anticipated from theory and prior evidence, not observed estimates. The expected pattern is that AI adoption raises productivity indirectly, through AI competence, organizational support and work engagement, and that its benefits weaken where technostress is high and psychological safety is low. The paper recommends integrating AI-competency training with well-being provision, organizational counselling services and evidence-based institutional policy. These actions support SDGs 3, 4, 8 and 9