How AI is Automating Data Cleaning and Feature Engineering in Data Science Pipelines

Revolutionizing Data Preparation with AI-Powered Tools and Techniques

Abstract

Data preparation—including cleaning and feature engineering—has long been one of the most time-consuming yet critical stages in the data science workflow. Traditionally done manually, it demands a large share of time and is prone to human error. As datasets grow in volume and complexity, the need for automated, intelligent solutions becomes increasingly urgent. This article explores how Artificial Intelligence (AI) is revolutionizing this space. From anomaly detection and semantic matching to AutoML-driven feature generation and AI-guided selection techniques, AI is accelerating and enhancing the quality of data preparation. Through practical tools, case studies, and forward-looking trends, we show how AI not only saves time but improves accuracy, scalability, and reproducibility, while freeing human analysts to focus on higher-value tasks.