The purpose of this study is to examine the impact of blockchain technology on taxpayer compliance among U.S. taxpayers, using it as a case study. It aims to explore the critical factors affecting blockchain technology applications in tax compliance systems. We first utilized a panel data model to establish empirical parameters linking audit intensity and qualification rates of Internal Revenue Service (IRS) tax returns. We then applied these parameters to an agent-based simulation model powered by artificial intelligence. We showed that integrating blockchain technology can effectively address noncooperative behavior and reduce the tax gap. Moreover, we identified two key factors—the improvement of the IRS’s efficiency and increased punishment—that can accelerate the development of blockchain technology in the tax compliance system. Our research adds to the existing literature on applications of agent-based simulation models in tax compliance systems and provides policy implications for promoting the use of blockchain technology.

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