Blockchain-integrated MLOps proposed for decentralized AI infrastructure

[TechRxiv] A preprint by Jessica Sciammarelli, dated March 5, 2026, proposes a decentralized AI infrastructure model that integrates blockchain into machine learning operations (MLOps) workflows to enhance data governance, model traceability and lifecycle transparency. According to the article, modern AI systems rely on complex infrastructure stacks spanning data pipelines, MLOps and cloud services, and centralized control of these components introduces risks related to data manipulation, lack of traceability and governance failures. The model uses smart contracts to enforce governance policies, control access to datasets and register model artifacts throughout their lifecycle. The article says the proposed architecture shows how blockchain can complement existing AI infrastructure by providing decentralized coordination, auditability and policy enforcement without compromising performance or scalability. The work is a preprint and has not been peer-reviewed.