Beyond Automation: Integrating Blockchain with Artificial Intelligence

Beyond Automation explores the powerful convergence of Blockchain and Artificial Intelligence, moving past isolated automation toward intelligent, trustworthy, and decentralized digital systems. Designed as a comprehensive academic and professional reference, this book explains how AI and Blockchain complement each other to solve critical challenges of trust, transparency, scalability, and accountability.
The book begins by building strong conceptual foundations in both Blockchain and AI, clearly explaining their evolution, limitations, and the motivation for integration. It then dives deep into how Blockchain can enhance AI systems through explainability, auditability, data provenance, and bias accountability, while AI strengthens Blockchain through intelligent consensus, fraud detection, smart contract security, and predictive optimization.
Real-world relevance is emphasized through detailed architectures, federated learning models, edge intelligence, and interoperability frameworks. Dedicated chapters examine high-impact applications in healthcare, finance, IoT, cybersecurity, and digital identity, supported by case studies and deployment insights.
Ethical, legal, governance, and performance considerations are treated with equal rigor, addressing regulatory compliance, privacy, scalability, and energy efficiency. The book concludes by exploring emerging trends such as Web3, metaverse systems, quantum implications, and self-learning smart contracts.
Beyond Automation is ideal for students, researchers, engineers, architects, and decision-makers seeking a structured, future-ready guide to building intelligent, secure, and decentralized systems powered by AI–Blockchain integration.