In fact, rapid convergence between Education 4.0 and Industry 4.0 demands adaptive learning models that would equip people with future-ready skills in the dynamically changing workforce. This work introduces AI-augmented skill development roadmaps, underlining how to design and implement personalized 12-month learning paths. The proposed framework is based on data-driven learner profiling, machine learning algorithms, and continuous adaptive assessments for optimization of building individual learning pathways toward emerging technology trends alignment. This review will be predicated on existing AI applications in competency development, identifying gaps in conventional models. It also involves the holistic roadmap structure: milestones, phases, and progression metrics. Case studies of real-world examples would then be delivered where AI-powered learning pathways have resulted in targeted competency development, employability, and lifelong learning. The key performance indicators will be defined to provide the effectiveness of the framework for scalability and adaptability. The findings bring to the fore that AI can cause a paradigm shift in skill gaps through enabling personalized learning at scale and furthering strategic goals related to Industry 4.0. This research makes a substantial contribution to the development of scalable education models for essential competencies that are part of the fast-evolving facets of digitalization. © 2024 IEEE.
Author Keywords
Index Keywords
