Mid Sweden University

Lifelong learning is essential for personal growth and societal progress. By continuously developing their skills, individuals can adapt to changes and drive progress. In this context, Artificial Intelligence (AI) enhances lifelong learning by offering personalised experiences, improving accessibility, and supporting continuous education (Escotet, 2024; Fahimirad &Kotamjani, 2018). This study explores AI’s role in lifelong learning, focusing on its tools, benefits, and opportunities for personalised education and skill development. The study also explores how AI can help bridge learning gaps and support learners at various points throughout their educational journey. 

A systematic literature review was conducted in accordance with the guidelines set by Page et al. (2021) to provide a comprehensive overview of current research on AI and its role in advancing lifelong learning. This study’s approach is guided by the standards set by the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA, February 21, 2024). The Scopus database was used to search for articles related to the study’s aim over a 10-year period in English in the field of social sciences. The search string applied in the systematic search was: (“Artificial Intelligence” OR “AI”) AND (“Lifelong learning” OR“continuous education”) AND (“personalised learning” OR “skill development”). A total of 60 studies were selected.

The preliminary findings suggest that diverse groups bring different perspectives on AI’s use, influencing its design and effectiveness in supporting lifelong learning. AI-powered tools are impacted by social and cultural forces, influencing their design and effectiveness in supporting lifelong learning (Eynon & Young, 2021). AI enhances lifelong learning by offering personalised learning tools that allow learners to progress at their own pace. Adaptive learning platforms provide customised content and real-time feedback, supporting skill development (Poquet & de Laat, 2021). AI should prioritise the development of learners ' capabilities rather than simply improving productivity. Bekmanova et al. (2021) propose a flexible model for blended and distance learning, where students take a test before starting, creating an individual learning path. This approach personalises learning in higher education, assigning mandatory and optional modules based on student performance. Luckin (2025) argues that AI has the potential to transform education by providing personalized learning experiences, enhancing teacher development, and automating tasks. However, the integration of AI should be balanced with the human touch in education to ensure that critical thinking, creativity, and problem-solving skills are nurtured.

As the review progresses, the findings will be categorised into themes to provide a clear understanding of the key patterns and trends emerging from the literature.