The Convergence of Big Data and AI Through Learning-Based Methods for Business Intelligence

The combination of big data and artificial intelligence (AI) is redefining how organizations learn from information by enabling systems that autonomously discover patterns, adapt to change, and generate valuable insights. This article presents overview of three AI applications areas for big data and then discusses one of these in depth using three potential transformative AI methods for learning-based methods: (1) federated learning for privacy-preserving customer behavior analysis, (2) self-supervised learning for detecting anomalies and fraud without labeled data, and (3) contrastive learning for creating robust representations that enhance personalization and recommendations. Together, these methods show how advanced learning paradigms extract actionable intelligence from distributed, unlabeled, and complex data while meeting ethical and regulatory standards.