Amid growing concerns over ethical sourcing, regulatory compliance, and operational transparency, global supply chains are under mounting pressure to adopt intelligent and accountable systems. Artificial Intelligence (AI) has emerged as a pivotal enabler in addressing these challenges, particularly within the context of digital transformation and sustainability. This study conducts a comprehensive bibliometric analysis to examine the evolving role of AI in driving accountability and transparency within global supply chains, while critically exploring the persistent gap between academic research and practical implementation. Drawing on 421 peer-reviewed articles published between 1998 and January 2025, extracted from Scopus and Web of Science, the analysis utilizes VOSviewer for network visualization and clustering. The findings reveal an exponential growth of research in this domain, particularly after 2020, driven by technological advancements and increasing regulatory pressures for transparency and ethical governance. The geographical distribution of contributions highlights India, China, and the United States as dominant knowledge producers, alongside growing engagement from emerging economies such as Malaysia and Morocco. The keyword analysis and thematic clustering uncover four key research streams: foundational AI technologies (e.g., blockchain, machine learning, IoT), AI-driven decision-making, blockchain-AI integration for supply chain transparency, and AI-IoT synergy within sustainable and circular economy frameworks. Beyond mapping intellectual structures and research trends, this study identifies a persistent gap between theory and practice. While technological solutions have advanced rapidly, organizational readiness, governance challenges, and ethical considerations remain underexplored. Addressing these gaps requires future research to adopt more integrative frameworks that link technological innovation with managerial practices, regulatory frameworks, and socio-cultural contexts, particularly in emerging markets. This study contributes to the literature by providing a structured overview of global research developments and by offering valuable insights for academics, practitioners, and policymakers aiming to foster responsible, inclusive, and context-sensitive AI adoption in supply chain governance.