Digital Transformation in Taxation: The Role of Artificial Intelligence and Big Data in the Modernization of Fiscal Administration, 2024.

Resumen

This study examines the impact of digital transformation on tax administration through the integration of artificial intelligence (AI) and big data. By analyzing case studies from various countries, the study highlights how AI algorithms and data analytics improve decision-making, risk assessment, and taxpayer services. AI allows for the analysis of vast amounts of data, identifying tax risks in real-time, and optimizing audits with predictive algorithms. Bigdata enhances the integration of diverse information sources, enabling tax authorities to design evidence- based policies that improve tax compliance and efficiency. This transformation is modernizing fiscal systems, offering new opportunities for automation, precision, and speed in detecting tax fraud and enhancing operational performance. However, it also raises several challenges, particularly regarding data privacy, algorithmic bias, and fairness in theapplication of tax regulations. The widespread use of AI and big data in tax administration presents ethical concerns about the protection of personal information, the transparency of algorithmic decisions, and the potential for discriminatory decision-making, especially if the underlying algorithms are not properly calibrated or audited. Moreover, there is a need for ensuring taxpayer acceptance and trust in automated systems, which may face resistance due to concerns about privacy and fairness. This paper discusses these challenges in detail while underscoring the need for a strategic framework to guide the effective and equitable adoption of these technologies. By implementing AI and big data strategically, tax administrations can enhance their capacity to generate sustainable revenue, optimize taxpayer services, and ensure more inclusive and efficient tax systems.