DECENTRALIZED AI INFRASTRUCTURE: INTEGRATING BLOCKCHAIN WITH MLOPS AND DATA GOVERNANCE (REMUNOM, 2026)
Modern AI systems rely on complex infrastructure stacks involving data pipelines, machine learning operations (MLOps), and cloud services. However, centralized control of these components introduces risks related to data manipulation, lack of traceability, and governance failures. This article presents a decentralized AI infrastructure model where blockchain is integrated into MLOps workflows to enhance data governance, model traceability, and lifecycle transparency. Smart contracts are used to enforce governance policies, control access to datasets, and register model artifacts throughout their lifecycle. The proposed architecture demonstrates how blockchain can complement existing AI infrastructure by providing decentralized coordination, auditability, and policy enforcement without compromising performance or scalability.