Artificial Intelligence and Taxation
Keywords:
taxation, artificial intelligence, global minimum tax, advance tax ruling, tax adviceAbstract
The examination of artificial intelligence and taxation is critical, as technology is fundamentally transforming the relationship between taxpayers and tax authorities, as well as compliance processes. Artificial intelligence can automate routine tasks (such as data entry and preparing returns), which can reduce errors and increase efficiency. Tax teams currently spend a significant amount of their time collecting and manipulating data, which artificial intelligence can do in a fraction of the time. Automation allows professionals to focus on higher value-added analytical and advisory tasks. Tax authorities actively use artificial intelligence for predictive analytics and network research to detect suspected tax evasion and fraud. Artificial intelligence helps analyse large amounts of financial data and identify suspicious patterns, making audits faster and more accurate. The introduction of a global minimum tax is an extremely complex and data-intensive process, for which multinational companies use artificial intelligence-based software to automate calculations and predict tax burdens. Companies that do not integrate artificial intelligence may find themselves at a significant competitive disadvantage. It is important to examine the legal and ethical framework for the use of artificial intelligence in taxation, ensuring transparency, data protection and algorithmic impartiality to avoid discriminatory bias. Examining this topic is essential for preparing future-proof tax systems and tax professionals in a rapidly changing, technology-driven world.
References
[1] The Organisation for Economic Cooperation and Development (OECD) is an international economic organisation based in Paris, whose aim is to assist member governments in developing and evaluating the best possible economic and social policies.
[2] Niels JOHANNESEN “The global minimum tax” Journal of Public Economics. Volume 212, August 2022, 104709, https://doi.org/10.1016/j.jpubeco.2022.104709
[3] Chee Yeow LIM; Terry SHEVLIN; Kun WANG; Yanping XU “Tax knowledge diffusion through individual auditor network ties: Evidence from China”. 2018. Singapore. https://doi.org/10.2139/ssrn.3229564
[4] Ildikó SZABÓ “Possibilities and Practical Experiences of Using Artificial Intelligence in Taxation” PÁZMÁNY LAW REVIEW 11:1 pp 53-66., 14p. (2024)
https://doi.org/10.55019/plr.2024.1.53-66
[5] Ildikó SZABÓ: Advance Tax Ruling in the domestic and international dimensions. In: Ács Kamilla; Bencze, Noémi; Bódog, Ferenc; Haffner, Tamás; Hegyi, Dávid; Horváth, Orsolya Melinda; Hüber, Gabriella Margit; Kovács, Áron; Kis Kelemen, Bence; Lajkó, Adrienn; Schilli, Gabriella Krisztina; Szendi, Anna; Szilágyi, Tamás Gábor; Varga, Zoltán (eds.) “5th Interdisciplinary Doctoral Conference: Book of abstracts” (2016) 206 p. pp. 57-57., 1 p.
[6] Ali Tofan, Rezza Vitriya, Galuh Tiaramurti “AI Integration in Tax Consulting Services: Technology Innovation or a Threat to the Profession?” Risenologi Vol. 10 No. 2 (2025)
https://doi.org/10.21009/risenologi.102.10
[7] Edwards, B. I., Cheok, A. D. (2018) “Why Not Robot Teachers: Artificial Intelligence for Addressing Teacher Shortage” Applied Artificial Intelligence, 32(4), 345–360. https://doi.org/10.1080/08839514.2018.1464286
[8] L. Zhang and L. Zhang “Artificial Intelligence for Remote Sensing Data Analysis: A review of challenges and opportunities” IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 2, pp. 270-294, June 2022, doi: 10.1109/MGRS.2022.3145854
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