Generative AI and Taxation―From Robot Taxation to AI Applications

Tetsuya Watanabe
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Tetsuya Watanabe: Professor, School of Law, Waseda University

Public Policy Review, 2025, vol. 21, issue 2, 1-18

Abstract: This paper analyzes the impact of the evolution of robots and generative AI on taxation from various perspectives as society becomes more digitized after the COVID-19 Pandemic. Specifically, in addition to the pros and cons of taxation on robots and generative AI themselves, I will examine what kind of use AI can be for tax authorities and taxpayers (including practitioners such as tax accountants); in other words, in terms of how all parties are affect- ed by the emergence of generative AI, and how they should interact with it in the future. Taxation on robots has been proposed as a response to changes in the labor market associated with the evolution of these machines. Its main purpose is to tax as a proxy or for regulatory purposes. However, it is difficult to define the terms of “robot” or “automation,” etc. Even if the definition is successfully clarified, taxation may be avoidable without international coordination, while the promotion of technology in countries where robot taxation is introduced might be hindered. Regarding the possibility of taxing AI itself, there are some proposals to give AI a taxable personality in certain cases where it has economic autonomy. For taxpayers and practitioners, generative AI could be a useful tool. However, from the standpoint of legal liability, it is currently difficult for AI to replace tax accountants in individual specific consultations. In addition, issues related to privacy protection and data collection and management have also been pointed out. In the future, the question of how to utilize AI in the environment surrounding the taxation issue will require deeper consideration.

Keywords: robotic taxation; generative AI; digitalization; innovation; tax administration; disparity (search for similar items in EconPapers)
JEL-codes: K34 (search for similar items in EconPapers)
Date: 2025
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