Auditing is a crucial component of the supervision system of the Party and the nation. The governance modernization and data intelligentization represent pivotal propositions that need to be solved for development of the scientific and standardized auditing in the new era. Based on the theoretical framework of Complex Adaptive System (CAS), this paper analyzes the laws of adaptive evolution of multi-level subjects in the national auditing system, and on this basis, constructs a four-dimensional collaborative theoretical model of “technology-process-mechanism-institution” for Scientific and Standardized Auditing. By deconstructing the technical core of the DeepSeek large language model, the coupling relationship between its dynamic decisionmaking ability driven by technical optimization and the evolution requirements of scientific and standardized auditing is revealed: break through the bottleneck of experience solidification at the technical level, eliminate the chronic problem of fragmented execution at the process level, bridge the gap of mechanism dispersion at the mechanism level, and overcome the constraint of institutional lag at the institutional level. The research proposes a deeply interembedded path between DeepSeek and scientific and standardized auditing, providing a theoretical paradigm and methodological support for addressing the adaptive limitations of traditional auditing models, improving the quality and efficiency of audit supervision, and building a centralized and unified, comprehensive and coverage, authoritative and efficient auditing supervision system.