In the complex and changeable social transition period, public policy, as one of the important means for the government to regulate the interest relationship among social members and realize the rational distribution of public interests and specific administrative objectives, is playing an increasingly important role. China is currently in the period of economic transition, which inevitably involves how to use a reasonable decision-making model to formulate scientific and effective public policies. Based on the perspective of public policy cycle theory, this article proposes an analytical framework for the impact and application of artificial intelligence algorithms on four stages of public policy: problem definition and agenda setting, policy formulation, policy execution, and policy evaluation. It points out that artificial intelligence algorithms have played a huge role in improving the scientific, accurate, and effective nature of public decision-making through their big data processing and predictive analysis capabilities. We have constructed the "S-R-P" theoretical model of China's open data policy in the big data environment, as well as its demand layer, decision-making layer, and operation layer submodels, to adjust existing policy demands through the operation of two circular paths. The result of model operation is not necessarily the introduction of specialized open data policies, which is also the essential difference between the "S-R-P" theoretical model and the general public policy theoretical model.