In recent years, the rapid development of next−generation information technologies has propelled artificial intelligence (AI) from a versatile technical tool to a strategic cornerstone driving the emergence of new productive forces and reshaping national technological competitiveness. AI's role is undergoing a profound shift—from an "enabler" to a "definer"—fundamentally transforming research paradigms and trajectories in interdisciplinary fields. This paper systematically traces the five evolutionary stages of scientific research paradigms, focusing on the fifth: AI for Science (AI4S). Centered on AI−driven innovation, AI4S integrates advanced technologies (e.g., convolutional neural networks, graph neural networks, diffusion models, large models) to systematically reconstruct scientific logics and technological pathways in frontier disciplines, including biomedicine, humanoid robotics, and quantum science. By doing so, it realizes intelligent transformation across the entire research lifecycle. The study underscores that authentic AI4S embodies a synergistic fusion of human creativity and scientific exploration. By automating repetitive tasks (e.g., low−level reasoning, experimental design), AI empowers researchers to concentrate on high−level problem formulation and strategic scientific planning, accelerating discoveries and breakthroughs. Human ingenuity remains the bedrock of science; free exploration and original theorization are indispensable. Through human−AI collaboration, AI4S propels scientific research toward higher−order intelligence and interdisciplinary integration, defining the future of technological advancement.