The Convergence of Artificial Intelligence and Blockchain in Financial Systems: Opportunities, Challenges, and Future Directions

Abstract

Artificial Intelligence and blockchain are converging in ways that are quietly reshaping how financial systems operate. AI brings predictive analytics, automated decision-making, and fraud detection; blockchain contributes an immutable, decentralised record that can be independently verified. Taken together, applications such as AI-augmented smart contracts and blockchain-anchored data pipelines are already changing how fraud is detected, how compliance is handled, and how decentralised finance (DeFi) functions. But the same combination that makes these systems powerful also makes them harder to govern: technical, regulatory, and ethical obstacles still stand in the way of adoption at scale. This paper uses a targeted, purposive literature synthesis alongside exploratory case analysis of financial institutions and fintech platforms to examine how AI and blockchain are transforming finance together, what barriers and systemic risks accompany that transformation, and where research and regulation need to go next. Drawing on the Technology Acceptance Model, Diffusion of Innovation Theory, and the Socio-Technical Systems perspective, the paper builds a multi-level framework for thinking about how AI–blockchain convergence can be adopted responsibly across the financial industry.