<p>The steel industry, characterized by its broad applicability, relatively low production cost, and strategic importance, is one of the pillar industries underpinning modern society. Over the past few decades, steel enterprises have undergone substantial transformation in automation and digitalization, significantly improving production efficiency and operational performance. With the rise of Industry 4.0 and the growing demand for sustainable and coordinated development, there is an increasing need to further integrate information technologies with industrial processes to accelerate the realization of automated, digital, and intelligent manufacturing. Against this backdrop, this paper provides a comprehensive review of artificial intelligence applications in the intelligent development of steelmaking processes. It categorizes the existing studies into several major application areas, including quality prediction, operational optimization, process monitoring, and anomaly diagnosis. The paper also discusses current challenges, potential solutions, and future research directions. This review aims to clarify the evolving relationship between steelmaking processes and artificial intelligence technologies and to support the transformation of the steel industry toward greener, lower-carbon, and more intelligent production. Furthermore, a forward-looking perspective is presented for the construction of a novel steel manufacturing paradigm in the Industry 5.0 era, characterized by ecological resilience, digital twin capabilities, and closed-loop resource recycling.</p>