The rapid, nonlinear evolution and crossdomain penetration of artificial intelligence (AI) have precipitated significant governance deficits, manifesting as “timing dilemmas” for regulatory intervention and “miscalibrated intensity risks” These challenges expose the limitations of traditional static and linear regulatory paradigms, trapping them within the “control dilemma” articulated by the Collingridge dilemma This paper constructs a dynamic governance framework predicated on the coupling of temporality and proportionality Through a historical analysis of disruptive technology regulation and a comparative study of the European Union, the United States, the United Kingdom, and China, the research identifies persistent key constraints: insufficient information and limited control, rendering purely precautionary or laissezfaire approaches inadequate Consequently, the paper proposes a threestage rolling intervention mechanism triggered by social penetration rate and contextual sensitivity, alongside a fourtier riskcalibrated toolkit grounded in the principle of proportionality This framework is supported by complementary measures such as evaluation and auditing systems, clear accountability chains, and international procedural mutual recognition, aiming to achieve a dynamic equilibrium between fostering innovation and ensuring safety