Integrating Artificial Intelligence and Blockchain: A Framework for Deep Learning Innovations and Future Directions
TL;DR
A formal taxonomy that systematically maps deep learning architectures to blockchain functionalities and application domains, enabling structured comparison of their complementary roles in fraud detection, consensus protocol optimization, smart contract automation, scalability, and data security is proposed.
Abstract
Blockchain technology and artificial intelligence (AI) has enhancing security, scalability, and transparency that potential to spur major developments in such industries as healthcare, finance, and supply chains. Although revolutionary, trust, scalability, and data privacy issues represent major impediments to their complete integration. Few works consider how blockchain and AI can be complementary, especially with regards to deep learning application in blockchain systems. Instead, most existing studies address these two subjects separately. Deep learning and a wide research agenda are the impetus behind this article's systematic review, which categorizes existing research, identifies major barriers, and proposes future directions of research. In a formal taxonomy that systematically maps deep learning architectures to blockchain functionalities and application domains, enabling structured comparison of their complementary roles in fraud detection, consensus protocol optimization, smart contract automation, scalability, and data security. In addition, the proposed research roadmap organizes short-, medium-, and long-term research directions by linking identified technical and non-technical challenges with emerging AI–Blockchain applications, thereby providing a structured foundation for developing secure, scalable, interoperable, and intelligent decentralized systems. The integration of deep learning with blockchain can protected data-flow management in peer-to-peer DeFi networks by enabling intelligent transaction analysis, anomaly detection, and decentralized verification while preserving data integrity and trust. This review addresses interdisciplinary research and provides an integrated solution, as opposed to traditional methods that address AI and blockchain as two different fields. The proposed roadmap bridges gaps in research, improves scalability, and guides future research towards the intersection of blockchain and artificial intelligence.