457. Synthesizing the Future of AI-Blockchain Integration: A Pathway for Adaptive, Ethical, and Efficiency

Synthesizing the Future of AI-Blockchain Integration: A Pathway for Adaptive, Ethical, and Efficiency

Keywords: Blockchain, Artificial Intelligence, Smart Contracts, Consensus Mechanisms, Distributed Ledger, Deep Learning, Formal Verification.

Abstract

This study systematically examines the transformative role of Artificial Intelligence (AI) in addressing the persistent challenges of blockchain technology across protocols, smart contracts, and distributed ledger management. Although blockchain offers decentralization, immutability, and transparency, its broader adoption remains constrained by scalability limitations, security vulnerabilities, inefficient consensus mechanisms, and the complexity of contract design and auditing. The findings of this review demonstrate that AI provides promising solutions to these barriers. Reinforcement learning (RL) applied to Proof-of-Stake reduced consensus latency by 30-50%, while NLP-based smart contracts lowered vulnerabilities by up to 40%, though both approaches introduced new concerns related to energy overheads and auditability. In addition, intelligent algorithms enhance ledger efficiency and data analytics, supporting more scalable and secure transaction processing. This Drawing on 28 peer-reviewed studies published between 2018 and 2024 and guided by the PRISMA 2020 framework, this paper synthesizes state-of-the-art research, maps sector-specific applications in finance, healthcare, and supply chain management, and highlights unresolved gaps in ethics, reproducibility, and regulatory compliance. Notably, only 12% of the reviewed studies validated their approaches on live networks underscoring the gap between simulation-driven research and real-world deployment. The discussion culminates in the AI–Blockchain Interaction Model (AIBIM), a conceptual framework that systematizes synergies across consensus, contract, and application layers. By integrating empirical insights with critical evaluation, this work emphasizes the interdisciplinary nature of AI–blockchain research and provides actionable directions for advancing decentralized, scalable, and ethically aligned systems. This synthesis provides actionable insights for developers, regulators, and researchers in deploying AI-blockchain systems across finance, healthcare, and supply chains.

DOI

Accepted
2025-08-19
Mandinyenya, G., & Malele, V. (2026). Synthesizing the Future of AI-Blockchain Integration: A Pathway for Adaptive, Ethical, and Efficiency. En Latin-American Journal of Computing (Vol. 13, Número 1). Escuela Politécnica Nacional. https://doi.org/10.5281/zenodo.17288802.
Section
Research Articles for the Next Issue (Early Access)