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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">GEDS</journal-id><journal-title-group><journal-title>Global Education Development Study</journal-title></journal-title-group><issn>3083-3973</issn><eissn>3083-3965</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/geds.v2i1.14433</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>AI Empowers Lifelong Learning: Technological Pathways, Future Skill Reconstruction, and Practical Cases </title><url>https://artdesignp.com/journal/GEDS/2/1/10.26689/geds.v2i1.14433</url><author>ZhangLuyang</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>2</volume><issue>1</issue><history><date date-type="pub"><published-time>2026-04-07</published-time></date></history><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.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Cai H, Wang J, 2025, Research on the Path of Artificial Intelligence Empowering Lifelong Learning in the Context of Digital Transformation. 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