Abstract: Spanning across disciplines with research interests in fundamental matter, life forms, and societal dynamics, the study of complex systems plays a pivotal role in deciphering and forecasting natural and social phenomena, thereby confronting intricate problems of human concern. The wealth of diverse real-world complex system data accumulated through early research has paved the way for a novel paradigm in complexity science research, which is intensively data-driven and steered by Artificial Intelligence (AI) methodologies. This innovative approach provides fresh insights into the characterization, forecasting, and knowledge extraction of complex systems. This article offers a visionary review of AI-driven studies in complex systems, highlighting the pioneering developments spearheaded by AI. It further scrutinizes exemplary works in the domain that leverage AI methodologies and concludes by contemplating the prospective evolution of AI theory and techniques under the lens of complex systems.