Leveraging Artificial Intelligence in zakat calculation: a comparative study of AI systems

Abstract

The integration of Artificial Intelligence (AI) into Islamic financial practices offers new avenues for enhancing zakat calculation accuracy, efficiency, and jurisprudential compliance. However, the adoption of AI in this domain raises complex questions regarding its alignment with Shariah principles, particularly in distinguishing between fixed rulings (nass) and interpretive jurisprudence (ijtihad). This study investigates whether AI can be leveraged to perform zakat calculations while maintaining doctrinal integrity. Using a qualitative research methodology, the study applies doctrinal analysis to classical Islamic sources and contemporary fatwas, combined with comparative analysis across the four major Sunni madhabs and a practical test of five AI systems: Claude, ChatGPT, Gemini, Perplexity, and Grok. Each AI was evaluated based on its ability to calculate zakat under three different scenarios of increasing complexity: basic cash, mixed portfolios, and modern instruments like cryptocurrency and REITs. The findings indicate that AI systems are capable of handling standard zakat computations with a high degree of accuracy and efficiency, particularly in areas categorized as wasail (procedural means). However, the results also highlight key limitations, including the inability to autonomously handle new asset classifications or apply jurisprudential discretion without prior scholarly input. The study proposes guidelines and parameters to ensure AI implementation respects the immutable aspects of zakat while optimizing ijtihadi areas. These insights are vital for future Shariah-compliant AI developments in Islamic financ