Integrating AI Education and Human Motivation for Sustainable Construction Productivity in Developing Nations

Abstract

Construction sites in developing nations are not short of problems, but two that rarely appear in the same analysis are the slow uptake of artificial intelligence and the persistent failure to motivate the workers who would use it. This paper argues that treating these as separate challenges is itself a root cause of the productivity stagnation that plagues the sector. A systematic literature review (SLR) was conducted using PRISMA guidelines, synthesising 28 peer-reviewed studies published between 2018 and 2026 and retrieved from Scopus, Web of Science, and Google Scholar. Thematic analysis produced three interlocking findings: AI education is a necessary but insufficient condition for productivity improvement; motivation determines whether skills acquired through training are ever applied on site; and sustainable productivity outcomes require both to operate simultaneously within a supportive institutional environment. A conceptual framework integrating these three dimensions is developed and theorised through the lens of socio-technical systems theory and human capital theory. The paper concludes with targeted recommendations for policymakers, construction firms, and academics working in resource-constrained contexts where neither technology nor motivation alone has moved the productivity needle.