Author ORCID Identifier
Raja Jayaraman:
https://orcid.org/0000-0002-2749-2688
Document Type
Journal Article
Journal Article Version
Final Version / Publisher's PDF (peer-reviewed)
Publication Date
5-1-2026
Abstract
Large Language Models (LLMs) are increasingly embedded in intelligent systems across domains such as healthcare, finance, and smart infrastructure. However, their reliance on centralized data pipelines raises unresolved challenges concerning provenance, accountability, and verifiable trust. As the demand for transparent and regulation-aligned AI grows, these challenges have become central to the responsible deployment of intelligent systems. This review examines how blockchain technology can address them by introducing decentralized integrity, immutable audit trails, and cryptographic verification into the LLM lifecycle. Through a structured synthesis of current research, we identify conceptual and architectural gaps that limit trustworthy data management, inference authentication, and explainability. To bridge these gaps, a methodological framework is proposed that integrates blockchain mechanisms across the LLM pipeline using smart contracts, Merkle-based commitments, and decentralized storage. The framework's feasibility is demonstrated through an illustrative prototype, confirming its practical applicability for building verifiable and transparent AI infrastructures. We further outline application domains such as healthcare, smart cities, Industry 4.0, and supply-chain management, where blockchain-anchored LLMs can enhance auditability and regulatory compliance. The review concludes by highlighting key insights and challenges for future research, emphasizing the need for decentralized attestation models, scalable verification protocols, and governance mechanisms that advance accountable and privacy-preserving intelligent systems.
Published in
Expert Systems With Applications
Keywords
Blockchain, Data governance, Explainable AI, Intelligent systems, Large language models, Trustworthy AI
Copyright Notice
© 2026 A. Musamih, I. Yaqoob, K. Salah, et al., reuse allowed according to Creative Commons license.
License for Reuse
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Musamih, A., Yaqoob, I., Salah, K., Jayaraman, R., & Omar, M. (2026). Blockchain for Large Language Models (LLMs): Applications, Challenges, and Framework Implementation. Expert Systems With Applications, 308. https://doi.org/10.1016/j.eswa.2026.131100