The Integration of Machine Learning and Explainable AI and Business Digitization: Unleashing the Power of Data - A Review

Abstract

The integration of machine learning (ML) and explainable artificial intelligence (XAI) within business digitization is a critical area for innovation and enhanced decision-making. This review synthesizes recent literature, sourced from academic databases like IEEE Xplore, Springer, ScienceDirect, and PubMed, focusing on peer-reviewed studies from the last five years to ensure relevance. Key applications of ML across healthcare, finance, and marketing are explored, highlighting its ability to handle complex datasets and improve predictive accuracy. The review discusses AutoML for automating ML model building, making advanced analytics more accessible, and examines the synergy between ML and IoT in small and medium-sized enterprises (SMEs) for innovation and efficiency. Explainable AI (XAI)'s role in providing transparency, building trust, and ensuring ethical AI deployment in business is also underscored. The findings indicate that strategic ML and XAI use in business digitization enhances operational efficiency and decision-making, providing a comprehensive overview of current trends, applications, benefits, challenges, and future research directions.