A Review of Higher Education Artificial Intelligence Frameworks to Empower Industrial & Sustainable Competitiveness in the Global South

Abstract The Fifth Industrial Revolution is uniquely characterized by a paradigm shift towards Artificial Intelligence (AI) and Machine Learning (ML), rapidly and fundamentally altering the Industry 5.0 skillsets landscape. To combat workforce deficiencies, Higher Education (HEIs) must rapidly deploy Education 5.0 frameworks, such as AI-assisted curricula revamps that can align advanced computation with sustainable development. However, a critical AI implementation gap and asymmetry exist between the Global North and Global South, threatening the stability of international, interconnected trade markets. We present a rigorous bibliometric and review-centric comparative policy analysis to map the global landscape of AI-led educational and technical infrastructure across Tier I Global South leader economies: India, China, and Brazil. Using Scopus search with advanced inclusion and exclusion criteria, we quantitatively track how India’s massive STEM graduate pipelines, China’s state-backed Next Generation AI strategies, and Brazil’s decentralized AIED unplugged initiatives function as transformative industrial assets. Crucially, our bibliometric framework exposes a severe disconnect in contemporary engineering pedagogy: the failure to translate digitized, human-centric educational tools into cross-sector economic productivity. By mapping these empirical research clusters directly to critical global supply chains – including near-shoring, rare earths, and advanced power management, we capture an actionable, algorithmic roadmap to transition currently theoretical concepts into a resilient Society 5.0 architecture. Our data-driven framework provides global policymakers and researchers with a scalable, empirical blueprint to ensure and catalyze industrial competitiveness while fulfilling the United Nations Sustainable Development Goals (UN SDGs).