The integration of artificial intelligence (AI) into tax collection processes has emerged as a transformative approach in improving efficiency, accuracy and compliance for national governments. Despite its potential, literature on AI’s role in tax collection, especially in developing countries, remains scarce. This paper makes a contribution to this area by conducting a systematic literature review aimed at investigating the current state of AI implementation in tax collection in developing nations and identifying future research opportunities. The review synthesises findings from twenty selected studies published between 2014 and 2024. The findings indicate that AI facilitates tax compliance through its capacity to automate repetitive tasks, enhancing data processing capabilities and detecting anomalies for targeted enforcement efforts. Moreover, AI tools offer potential in reducing tax evasion by enabling real-time transaction analysis and value chain analysis, closing taxation loopholes and improving fraud detection mechanisms. However, responsible AI use remains paramount, necessitating the establishment of ethical frameworks, transparency measures and mechanisms for accountability to ensure user data protection and adherence to societal norms and legal standards. By compiling insights from diverse studies, this work presents a unique perspective and paves the way for additional research in this emerging field.
Mudome et al. (Wed,) studied this question.