Agentic AI vs. Traditional Machine Learning in Big Data Applications
Introduction In the era of big data, where organizations grapple with massive volumes of information generated at unprecedented speeds, artificial intelligence (AI) technologies have become indispensable for extracting value and driving decisions. Traditional machine learning (ML) has long been the cornerstone of data analysis, enabling predictive modeling and pattern recognition. However, the emergence of agentic AI represents a paradigm shift toward more autonomous, goal-oriented systems capable of handling complex, dynamic environments. This chapter explores the definitions, differences, advantages, challenges, and applications of agentic AI compared to traditional ML in big data contexts, highlighting how these technologies are transforming industries. Understanding Traditional Machine Learning Traditional machine learning encompasses algorithms that learn from data to make predictions or decisions without being explicitly programmed for each task. It includes supervise...