Artificial Intelligence (AI) has demonstrated immense potential in the scientific domain. AI for Science (AI4S) is rapidly advancing and gaining widespread adoption, driving a comprehensive transformation in scientific research paradigms. However, the characteristics and mechanisms of AI4S in empowering scientific innovation remain unclear, and its strategic direction has yet to be systematically planned. Focusing on the 2024 Nobel Prize in Chemistry-winning projects, AlphaFold and Rosetta, this study employs a comparative case analysis to examine the distinct features and mechanisms of AI-enabled scientific research. It proposes two AI4S empowering models: "AI+" and "+AI." From the perspective of knowledge production modes, the study further analyzes the knowledge production characteristics of these two models. It identifies the emergence of "intelligence" as a fifth major actor in the "AI+" model, with knowledge production exhibiting traits of growth, independence, collaboration, and platformization. Additionally, the "AI+" and "+AI" models each have their own suitable application scenarios and frameworks. Finally, this paper offers policy recommendations, including differentiated strategies for AI+ and +AI, prioritizing small-model development, and advancing infrastructure construction. These findings contribute to both AI4S-related research and knowledge production mode theory, while also providing insights for China's development of the AI industry, exploration of AI applications, and advancement of AI models.