Digital readiness, trust, and collaboration: pathways to AI adoption in informal supply chain workers

Abstract

The study looks at the ways that digital readiness affects the adoption of artificial intelligence (AI) and, in turn, the improvement of livelihoods for informal supply-chain workers. It focuses on the mediating functions of collaborative strategies and trust in AI tools. A cross-sectional survey design was used to gather information from informal supply-chain workers. Within the suggested framework, hypotheses were examined for direct and indirect effects using the structural equation modeling (SEM)-based Smart PLS technique. The results support the hypothesized model. Digital readiness had a significant positive influence on trust in AI tools, collaborative strategies, and AI adoption. Both trust and collaboration were found to be significant direct antecedents of AI adoption. Crucially, the relationships between digital readiness and AI adoption were partially mediated by trust and collaborative strategies, confirming that these factors are vital pathways. Finally, AI adoption showed a positive and significant relationship with improvement in overall livelihoods. However, there was a statistically nonsignificant direct relationship between digital readiness and livelihood improvement. This suggests that livelihood gains are achieved mostly by successful implementation of AI-supported tools and applications rather than through digital readiness alone. The outcomes of this study are particularly important for frontline workers, managers, and industry practitioners in the supply chain and strategy domains, as they show how integrating digital technologies into everyday work practices can improve efficiency, resilience, and long-term livelihood outcomes. Although the use of AI in informal supply chains is still modest, it offers a significant opportunity to improve livelihoods. Understanding the collaborative enablers that promote AI adoption among informal workers, who frequently operate with limited resources, represents a critical research gap.