A Review of Artificial Intelligence Integration in Higher Education and Its Implications for Organizational Control and Labour Process in Emerging Economies

Abstract The growing use of Artificial Intelligence (AI) in universities is altering how academic work is organized and governed, raising important questions about control and labour in higher education, particularly in emerging economies. Against this background, this paper reviewed artificial intelligence integration in higher education and examined its implications for organizational control and the labour process. The paper specifically examined the patterns and modes of artificial intelligence integration in higher education institutions in emerging economies, analyzed how artificial intelligence adoption shapes organizational control mechanisms within higher education institutions and investigated the effects of artificial intelligence integration on the labour process, The paper was guided by labour process theory, which provides a basis for understanding how technology reshapes managerial control and work relations. A systematic review design was adopted, drawing on recent scholarly publications between 2022 and 2026 sourced from peer-reviewed journals and policy reports. The findings showed that artificial intelligence is increasingly embedded in teaching, assessment, and administrative systems, with emerging economies adopting these tools within resource-constrained and centralized institutional settings. The paper revealed that AI adoption strengthens data-driven oversight, performance monitoring, and standardization of academic tasks, thereby reinforcing managerial control. At the same time, academic labour is being restructured through increased workload demands, digital skill requirements, and reduced autonomy in decision-making processes. While some gains are recorded in efficiency and instructional support, concerns persist regarding surveillance, job insecurity, and uneven capacity for adaptation across institutions. The paper concluded that artificial intelligence integration in higher education is not neutral but reflects existing power relations within institutions. The paper therefore recommended that there should be development of clear regulatory frameworks, inclusive governance structures, and capacity-building initiatives to ensure that AI deployment supports both institutional effectiveness and fair labour practices.