Trust dynamics for AI implementation in high-barrier environments: the moderating effect of government involvement

Purpose This study explores the intricate relationship between trust dynamics and AI implementation in high-barrier environments within emerging economies. It investigates how government involvement, organisational leadership, managerial competence and organisational readiness collectively shape trust in AI implementation capability (TOIC). By examining these interactions, the research aims to provide a nuanced understanding of how government involvement influences trust within the firm. Design/methodology/approach The study employs a conceptual framework grounded in the technology-organisation-environment (TOE) model, combined with a multilevel trust perspective. Data were collected through a survey of 412 information technology and information and communication technology (IT/ICT) firms and analysed using partial least squares structural equation modelling (PLS-SEM). This approach enabled the identification of key relationships and moderating effects between trust determinants and AI implementation. Findings Three key insights emerged: (1) Government involvement indirectly influences trust by enhancing organisational readiness but can reduce trust when perceived as intrusive; (2) Top management support serves as a critical trust driver by shaping organisational readiness and aligning AI strategies with operational realities and (3) Managerial competence mediates trust development by translating strategic goals into operational practices, particularly in environments with high perceived barriers. Research limitations/implications The study focuses on IT/ICT firms in Ghana, potentially limiting generalisability. Future research should explore these trust dynamics in diverse emerging markets to validate the findings and expand theoretical insights into AI adoption in high-barrier contexts. Practical implications The findings underscore the need for governments to foster organisational readiness through training and infrastructure development rather than direct intervention. For business leaders, investing in top management support and managerial competence can enhance trust and facilitate successful AI adoption. Social implications By clarifying the trust-building mechanisms for AI implementation, this research supports the development of policies that balance technological innovation with societal trust, ultimately contributing to more inclusive and sustainable technological progress. Originality/value This study extends the TOE framework by integrating trust as a core factor in AI implementation and highlighting the moderating effect of barriers. It offers practical insights into the paradoxical role of government involvement, demonstrating that trust in implementation capabilities is contingent on strategic alignment between policy initiatives and firm-level capabilities.