AI-powered integration: How machine learning is reshaping data pipelines

Baddam, Bharath Reddy (2025) AI-powered integration: How machine learning is reshaping data pipelines. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 1284-1290. ISSN 2582-8266

This article investigates how artificial intelligence and machine learning technologies are transforming traditional data integration processes into intelligent, self-optimizing systems. The evolution from rigid rule-based approaches to adaptive machine learning solutions represents a fundamental paradigm shift in enterprise information management. Organizations implementing AI-enhanced integration experience significant improvements in operational efficiency, error reduction, and throughput capacity while simultaneously reducing manual intervention requirements. As data environments grow increasingly complex, with organizations managing more diverse sources than ever before, these intelligent integration capabilities have evolved from optional enhancements to essential tools. The article examines core machine learning capabilities including intelligent data mapping, anomaly detection, and self-healing mechanisms, along with implementation approaches ranging from embedded platform solutions to custom components and hybrid architectures. While acknowledging important challenges related to data privacy, governance, model maintenance, and legacy system integration, the article demonstrates how AI-powered integration is reshaping data pipelines across industries.