AI-Enhanced Data Exchange Between Companies and Tax Authorities: a New Era for Compliance and Auditing

The rapid integration of Artificial Intelligence (AI) into financial and administrative systems marks a fundamental shift in how governments collect, analyze, and utilize tax data. This study explores the role of AI in enhancing the efficiency, transparency, and integrity of data exchange between companies and tax authorities, representing a transformative step toward real-time compliance and automated auditing. Drawing on secondary data from international organizations such as the OECD, World Bank, and IMF, as well as a review of case studies from Brazil, the European Union, and selected Asian economies, the paper investigates the evolving structure of tax data systems from traditional manual filings and electronic submissions to AI-based predictive frameworks. The findings reveal that AI-driven systems can significantly reduce administrative burdens, improve fraud detection accuracy, and enable continuous auditing through automated risk assessment tools. However, the study also identifies key challenges, including data privacy risks, cybersecurity vulnerabilities, algorithmic bias, and the technological divide affecting small and medium-sized enterprises (SMEs). Addressing these concerns requires not only advanced technical safeguards but also robust legal frameworks, transparent data governance, and cross-border cooperation among tax authorities. Ultimately, this study argues that AI-enhanced tax data exchange represents more than a technological innovation it redefines the principles of fiscal governance by fostering a proactive partnership between states and businesses. When implemented responsibly, AI offers a path toward more inclusive, transparent, and accountable financial systems capable of sustaining long-term economic trust.