Intelligent fluids represent a significant interdisciplinary convergence of chemistry, physics, control theory, artificial intelligence and engineering disciplines. These unique materials have the intrinsic capability to modify their physical properties, specifically viscosity, in response to external stimuli such as magnetic, electric, photonic, and thermal fields. This paper offers a holistic overview of the evolution, properties, and applications of distinct categories of artificial intelligent fluids: ferrofluids, magnetorheological, electrorheological, and photonic and thermoresponsive fluids. From their early historical contexts to their transformative roles in sectors ranging from automotive to biomedical, each fluid's potential is thoroughly explored. Artificial intelligence techniques, encompassing both deep learning and reinforcement learning, have facilitated the intricate modeling and control of these fluids. Furthermore, the challenges they face, from sedimentation concerns to environmental considerations, are discussed. As technological demands continue to pivot towards adaptability and efficiency, artificial intelligent fluids are poised to emerge as pivotal solutions. However, their successful integration necessitates a nuanced understanding, balancing their remarkable capabilities with the challenges they present.