A research team led by Qian-Yuan Tang from Hong Kong Baptist University and Weitong Ren from Wenzhou Institute, University of Chinese Academy of Sciences, has reviewed how artificial intelligence is shifting protein science from task-driven prediction toward principle-oriented discovery. They introduced a new concept of AI functioning as an observatory to explore the complex organization of proteins. Moving beyond mere prediction, this perspective leverages AI-derived signals to uncover underlying physical constraints, evolutionary patterns, and functional principles that shape protein structures and dynamics. By viewing AI models as tools for systematic observation, researchers can decode the organizational principles of proteins-paving the way for more informed bioengineering and therapeutic strategies.