In recent decades, the role of digital technologies in the transformation of countries' financial and economic governance systems has increased to the point that not utilizing them is considered a sign of structural backwardness. Iran's tax system is no exception to this rule, and in recent years it has faced fundamental challenges such as widespread tax evasion, lack of comprehensive transparency in financial transactions, lack of integration of information systems, complexity of administrative processes, and inequality of tax burden among different strata. In such circumstances, new financial technologies (FinTech) and artificial intelligence can accelerate the path of tax reforms by creating a revolution in data collection, intelligent information processing, discovering hidden patterns, and providing more efficient services to taxpayers. The purpose of this study is to examine the impact of new financial technologies and artificial intelligence on the transparency and efficiency of Iran's tax system and to provide an operational layered framework for implementing these technologies. The research method is descriptive-analytical and the data is extracted from reliable scientific sources, international policy documents and specialized reports. Tax transparency in this study means government access to real and timely data, reducing information asymmetry, transaction traceability, and increasing public trust. Efficiency also includes processing speed, reducing costs, improving the quality of processing, and promoting tax justice. Initial findings show that the use of tools such as electronic invoices, big data analysis, machine learning, blockchain, smart risk assessment systems, and fintech-based services to taxpayers can reduce the tax gap, strengthen tax law enforcement, and significantly increase transparency and efficiency. A proposed four-layer model including a data infrastructure layer, smart analysis layer, monitoring and control layer, and taxpayer services layer has been designed, which can be the basis for the operational planning of the Tax Affairs Organization.