That’s a very important and timely question. As Artificial Intelligence (AI) becomes more integrated into tax law enforcement, especially in countries with weak algorithmic oversight, we face serious challenges:

• Algorithmic bias: AI can unintentionally target certain groups unfairly.
• Lack of explainability: Many AI systems act like "black boxes," making decisions without transparency.
• Data privacy risks: Especially where data protection laws are not well-defined.
• Accountability gaps: It’s often unclear who is responsible for wrong or biased decisions—developers or enforcement agencies.

For a related perspective, I’d refer you to my article titled: “The Application of Artificial Intelligence in Credit Risk Evaluation: Obstacles and Opportunities in Path to Financial Justice” (Published March 2025, available on my ResearchGate profile – Ahmed Raza Siddiqui)

This article explores how AI’s use in credit risk systems can either reduce inequality or deepen it—depending on its transparency, fairness, and data quality. The same risks apply in AI-powered tax enforcement.

In both finance and tax, AI is only as just as the frameworks surrounding it. Without strong legal and ethical foundations, such tools can quickly turn from innovation into injustice.

Mohammadamir Modami I believe that global tax law is, at best, still catching up to the rapidly evolving landscape of AI-powered enforcement, especially in countries where there is weak algorithmic oversight. While the use of AI in enforcement can offer greater efficiency and precision in identifying tax fraud or non-compliance, I’m concerned that, in places with limited oversight, the risks could outweigh the benefits.

AI systems, if not carefully monitored and regulated, can inadvertently perpetuate biases, make errors, or even fail to account for the unique socio-economic factors that affect tax compliance. In countries with weak governance structures or insufficient algorithmic accountability, these risks are magnified. The AI models could unfairly target certain populations or lead to misapplications of tax laws, creating unfair burdens on taxpayers.

I also worry about the lack of transparency. AI systems often operate as "black boxes," meaning that their decision-making processes are not always clear to the public or even to the officials overseeing them. This makes it difficult to ensure fairness and accountability, particularly when those being targeted by the AI-powered enforcement systems have little recourse for challenging potentially erroneous decisions.

In my view, a strongg framework for algorithmic oversight and transparency is essential before AI-powered enforcement can be fully integrated into global tax systems, especially in countries with weaker legal infrastructure. Without this, the system could end up exacerbating inequalities, undermining trust in the tax system, and potentially violating fundamental rights. For global tax law to be truly ready for AI-powered enforcement, there needs to be a serious commitment to ethical AI practices, international collaboration, and the development of clear, transparent guidelines to safeguard against these risks.