Blockchain and Artificial Intelligence: Convergence, Applications and Challenges

Abstract

The integration of blockchain technology and artificial intelligence (AI) represents a transformative paradigm for intelligent decentralized systems. This review examines integrated blockchain–AI architectures that leverage AI's optimization capabilities to enhance blockchain scalability and security, while blockchain provides immutable data provenance and decentralized trust for AI systems. We explore applications across multiple domains including Internet of Things (IoT), finance, healthcare, secure information sharing, and supply chain management, with particular emphasis on blockchain and AI integration in clinical trials for improving patient recruitment, data integrity, and regulatory compliance. Furthermore, we analyse AI's role in blockchain governance, including optimization of decentralized autonomous organizations (DAOs) and automated compliance monitoring. Despite promising developments, significant challenges persist, including technical limitations such as computational overhead, interoperability constraints, and scalability issues, as well as critical data privacy and security concerns. This review provides a structured analysis of current blockchain-AI integration strategies and identifies key research directions for developing robust, secure, and ethically governed intelligent decentralized systems.