Democratizing Vocational Training: AI-Enabled Skill Development for Gig and Informal Workers

Abstract

More than sixty percent of the global workforce operates in informal or gig-based economies, yet these workers remain systematically excluded from structured upskilling systems that are increasingly essential in the AI-driven labor market. This study addresses this persistent exclusion by proposing and validating a tri-layer AI-enabled vocational training model designed to strengthen skill acquisition, learning efficiency, and employability outcomes for informal workers. The model integrates three mutually reinforcing components: a generative simulation layer that uses synthetic visual environments to replicate trade tasks; an adaptive feedback layer driven by transformer architectures that personalizes learning trajectories; and a labor analytics layer that connects performance metrics to workforce demand patterns.
To assess the expected effectiveness of this model, the study synthesizes empirical findings from VR-based training, AI-assisted learning systems, and international datasets from the ILO, UNESCO-UNEVOC, and World Bank meta-analyses. Benchmark evidence demonstrates that AI-enabled simulations substantially outperform conventional workshop training, yielding higher learning efficiency (78 percent compared to 42 percent), improved task accuracy (84 percent compared to 55 percent), and stronger adherence to safety procedures (83 percent compared to 48 percent). These improvements highlight the potential of generative and transformer-based systems to replicate the instructional value of apprenticeship-style mentoring at scale.
The findings underscore that AI-driven vocational ecosystems can democratize access to high-quality technical learning, reduce skills inequality, and support national strategies aligned with SDG 4. However, achieving equitable deployment requires prioritizing low-cost delivery models, localized content, multilingual interfaces, and strong governance frameworks to safeguard learner data and ensure inclusion. Overall, the study provides a validated conceptual and analytical foundation for integrating generative AI into informal workforce training, demonstrating its promise as a scalable and socially transformative instrument for future-ready skill development.