Aiming at the current problem of corporate tax avoidance in tax collection and management, this study explores how to optimize tax collection and management through digital transformation. Taking the data of China's A-share non-financial listed companies from 2010 to 2023 as a sample, we analyze the impact of digital transformation on corporate tax avoidance behavior and its internal mechanism. First, the establishment of local big data bureaus is used as a quasi-natural experiment to quantify the governance effect of digital transformation using the double difference method (DID). Subsequently, the robustness of the estimation results is ensured by parallel trend tests and placebo tests. The study shows that digital transformation significantly reduces corporate tax avoidance, as evidenced by an increase in the effective tax rate (ETR) and a decrease in the book-to-date (BTD) and nominal-to-actual tax rate differences (TA). Mechanism analysis shows that digital transformation reduces the space and incentives for corporate tax avoidance by strengthening joint tax audits, optimizing the business environment, and reducing institutional transaction costs. The study suggests that the government should deepen its digital strategy, promote cross-sectoral data sharing and collaboration, enhance tax supervision capabilities, and optimize the tax service system to incentivize proactive law-abiding behavior. Future research could further explore the applicability of different digital governance models in tax administration and their long-term impact.