AI Empowers Lifelong Learning: Technological Pathways, Future Skill Reconstruction, and Practical Cases

Abstract

As digital transformation deepens, artificial intelligence (AI) has emerged as a core driver of lifelong learning transformation. This paper focuses on exploring AI-empowered lifelong learning through three dimensions: technological pathways, future skill reconstruction, and practical cases. Regarding technological pathways, it constructs a four-dimensional interconnected system of “data-algorithm-application-governance”, analyzes the triple barriers of “technology-humanities-institutions” and proposes countermeasures, clarifying AI’s role in foundational data collection, full-process support at the application layer, and cross-scenario ecosystem construction. For future skill reconstruction, addressing the shift in talent demands from “static matching” to “dynamic adaptation” in the AI era, it proposes a three-dimensional skill system of “core competencies-professional skills-meta-abilities” and establishes a “trinity” collaborative implementation mechanism involving educational institutions, enterprises, and individuals. In terms of practical cases, it compares the inclusive practices of China’s National Open University’s AI+ lifelong learning platform with the precision-oriented exploration of Udacity’s nanodegrees abroad, extracting key insights on technology-demand alignment, skill-scenario integration, and multi-stakeholder ecosystem collaboration. Leveraging a “national-local-international” policy framework, it proposes four safeguard mechanisms: institutional, technological, supervisory, and equity-focused.