The convergence of blockchain technology and artificial intelligence represents one of the most transformative developments in modern computing, reshaping how intelligent systems are designed, deployed, and governed at scale. This textbook examines how the integration of these technologies addresses persistent challenges in trust, transparency, accountability, scalability, and intelligent decision-making that arise when each is used independently.
Blockchain has evolved from Bitcoin’s 2008 peer-to-peer cash system into a foundational infrastructure for decentralized trust, smart contracts, and verifiable record-keeping across industries such as finance, healthcare, supply chains, digital identity, and governance. In parallel, artificial intelligence has progressed from early rule-based systems to advanced deep learning and generative models capable of vision, language understanding, strategic reasoning, scientific discovery, and creative content generation. Despite their success, both technologies face serious limitations. Blockchain struggles with scalability, energy efficiency, limited computational flexibility, and usability. AI systems face challenges in transparency, data integrity, bias, accountability, and the concentration of power within centralized institutions.
Their integration offers powerful synergies. Blockchain enhances AI by providing verifiable data provenance, immutable audit trails, transparent model governance, and decentralized control. AI strengthens blockchain through optimized consensus mechanisms, vulnerability detection, fraud prevention, predictive analytics, and improved user experience. This textbook serves graduate students, researchers, and industry practitioners, providing foundational principles, interdisciplinary theory, practical applications, and future research directions essential for advancing blockchain–AI systems in real-world environments.