<![CDATA[The integration of Artificial Intelligence (AI) and Blockchain represents a paradigm shift in digital transformation, offering enhanced security, scalability, and automation. While previous research has explored these technologies independently, this study provides a comprehensive review of their convergence, synthesizing insights across multiple domains such as finance, healthcare, and supply chain management. The findings highlight the bidirectional enhancement of AI-Blockchain integration: Blockchain reinforces AI’s reliability by ensuring data immutability and transparency, whereas AI optimizes Blockchain efficiency through intelligent consensus mechanisms and fraud detection. However, significant challenges remain, including scalability constraints, computational overhead, and regulatory concerns. This study contributes to the theoretical understanding of AI-Blockchain synergy by integrating concepts from Computational Trust Theory and Decentralized Ledger Theory. Practically, it provides actionable insights for industry stakeholders, particularly in decentralized finance, privacy-preserving AI models, and secure digital transactions. The novelty of this research lies in its examination of AI-Blockchain integration through geographical and temporal trends, revealing disparities in adoption and regulatory responses. Despite its potential, real-world implementation remains limited, necessitating further empirical validation and exploration of emerging technologies such as quantum computing and the Internet of Things (IoT). By addressing these gaps, this study serves as a foundation for future research and policy development, advocating for interdisciplinary collaboration to ensure secure, efficient, and ethical AI-Blockchain ecosystems. The implications extend beyond academia, offering strategic guidance for practitioners and policymakers navigating the complexities of this technological convergence.]]>
Copyrights © 2025
