Meta analytic study of human AI co decision systems and workforce intelligence in enhancing sustainability performance in circular supply chains

Abstract

The shift to circular supply chains (CSC) in the context of Industry 4.0 has further driven the adoption of artificial intelligence (AI) for production planning, logistics and sustainability considerations. But an increasing body of evidence suggests that the environmental implications are less a matter of AI adoption and more about how effectively AI complements human judgment and human skills. The paper contributes by introducing a meta-analysis on the function of human–AI co-decision systems and labour intelligence as enablers for circular economy (CE) in production systems. Based on PRISMA-2020 checklist, 269 Scopus-indexed empirical studies published through 2018 to 2025 were systematically screened and meta-analyzed by applying random-effect meta-analytic method. The findings reveal a robust and positive association with statistical significance between human–AI co-decision systems and the adoption of circular behavior, which ultimately enhances environmental performance. Workforce intelligence, including digital skills, collaborative capability and organization learning readiness enhances these relationships. Models that are based on a closely working relationship of the human and AI system continue to outperform dominant AI models, as well as highly assistant systems. Social sustainability outcomes are enhanced the most, whereas economic gains are rather modest, proving real-world trade-offs in implementation. Together, the results underscore the significance of human-centric design of AI and workforce readiness in driving sustainable and resilient CSC.