Intelligent taxation and quantum computing: new paradigm in fiscal control

Authors

Keywords:

Smart taxation, quantum computing, artificial intelligence, Big Data, fiscal control

Abstract

Intelligent taxation, based on advanced technologies such as artificial intelligence and Big Data, enables the
analysis of large volumes of data, detects behavior patterns, and prevents tax fraud. On the other hand, quantum
computing, with its principles of superposition and quantum entanglement, offers unprecedented processing capabilities to solve complex problems. The integration of these technologies can transform tax management, improve tax collection, and strengthen fiscal transparency. Quantum cryptography, in particular, presents itself as a critical area, as it could compromise current cryptography and jeopardize banking systems and tax administration databases within minutes. Therefore, it is essential for tax administrations to embrace these new technologies, not only to enhance artificial intelligence tools that prevent fraud and evasion but also to protect their databases through quantum cryptography. The collaboration between intelligent taxation and quantum computing can facilitate the creation of more sophisticated predictive models, allowing for the anticipation of evasive behaviors and the design of proactive fiscal control strategies. However, this integration also presents significant challenges in terms of infrastructure, investment, and ethical considerations, which must be carefully addressed to ensure effectiveness and trust in the tax system. In summary, the combination of these technologies has the potential to revolutionize fiscal management, optimizing processes and strengthening transparency in tax administration.

Author Biography

  • Miguel Romero, Independent researcher


    miguelangelromeroduarte@gmail.com

Computación

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Published

2025-08-29

Issue

Section

Artículos científicos

How to Cite

Intelligent taxation and quantum computing: new paradigm in fiscal control. (2025). Observador Del Conocimiento, 10(5), 17-27. https://revistaoac-cal.oncti.gob.ve/index.php/ODC/article/view/320

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