A Review of Business Analytics, Machine Learning, and Generative Artificial Intelligence Research 2020–2025: Toward Responsible Artificial Intelligence

This review examines the evolving intersections of data analytics, machine learning, and artificial intelligence—terms that have been frequently conflated since 2016 during a period of increased hype and investment. Following recent reviews across areas such as open innovation, supply chain deep learning, strategic alliances, natural language processing, and big data streaming, we focus on the emerging field of Responsible Artificial Intelligence (AI). We apply descriptive analysis to identify trends, patterns, and gaps in the research through a review of academic literature from 2020 to 2025. Analysis reveals five distinct clusters of Responsible AI papers using five dimensions: fairness, cross-validity, transparency, accuracy–interpretability tradeoff, and drift detection. This review discusses patterns across the artificial intelligence literature and identifies future research opportunities with an emphasis on Responsible AI.