AI-enabled sustainable talent management for workforce stability: A systematic review on human capital, skill and retention in the era of twin transition.

As industries encounter the twin challenges of digital transformation and environmental sustainability, AI-driven talent management has emerged as a strategic facilitator for promoting sustainable human capital development and securing long-term workforce stability. This study explores the influence of artificial intelligence-driven talent management strategies to boost employee engagement and retention with the promotion of social, economic, environmental, and technological sustainability. The PRISMA framework utilized on the Scopus database (2005-2025) adopted predetermined inclusion and exclusion criteria, conducted independent dual screening (Cohen's κ = 0.76), and assessed study quality using MMAT to reduce selection bias and redundancy. The results underscore the revolutionary capacity of AI in harmonizing talent management with inclusive, human-centred methodologies for skill development, industrial empowerment, and sustainable talent retention strategies. This paper synthesizes 90 peer-reviewed articles and presents a conceptual framework titled 'AI-enabled Sustainable Talent Management for Retention', which includes sectoral and country-specific comparative assessments and insights into a stagewise adoption roadmap for educators, industry decision makers, and policymakers dedicated to cultivating a resilient and future-ready workforce in the context of the twin transition, by addressing Sustainable Development Goals such as SDG 8 (Decent Work and Economic Growth) and SDG 13 (Climate Action).