The sudden and rapid adoption of artificial intelligence in the world of work and jobs is transforming the way we train and develop skills globally. This trend makes adaptive and proactive vocational education more important than ever before (World Economic Forum, 2020; International Labour Organization, 2019). We understand that AI has the potential to personalize learning, enhance skill-job matching, and increase productivity, but the evidence is mixed. Specifically, we still have no clear, regional understanding of vocational ecosystems in developing countries (Zawacki-Richter et al., 2019). To fill this gap, this research undertakes a systematic literature review to compile global and Indian literature on AI-based workforce development, with a specific policy emphasis on the vocational education and training system in Maharashtra. Based on a PRISMA protocol, peer-reviewed literature from 2015 to 2025 was searched and examined in prominent academic databases. By thematic synthesis, this literature review investigates four interrelated themes:

(i) the adoption of AI in vocational and industrial contexts and emerging skill requirements (Autor, 2015; Acemoglu & Restrepo, 2020);

(ii) the effectiveness of AI-based learning platforms and competency analysis tools in bridging skill gaps and enhancing employability (OECD, 2021; World Economic Forum, 2023);

(iii) the challenges of ethics, governance, and capacity building in the use of AI in skilling systems (Floridi et al., 2018; Yeung, 2020);

(iv) the implications of AI integration for the long-term adaptability of the workforce and career sustainability (OECD, 2023).

Based on theories of behavioral economics, human capital, and socio-technical systems (Becker, 1993; Orlikowski, 1992), this research develops a novel framework that integrates AI-based skilling with institutional readiness and workforce resilience. The results demonstrate the high potential of AI in reshaping vocational education and training while simultaneously highlighting the existing shortcomings in regulatory preparedness, teacher capacity, and ethics. By situating the global evidence within the institutional and policy context of Maharashtra, this paper provides specific recommendations for policymakers, training institutions, and industry stakeholders. It contributes to theoretical debates on human-AI collaboration in workforce development and provides a specific roadmap for developing inclusive, ethical, and AI-ready skilling strategies for regional labor markets...