Building a Framework for Artificial Intelligence Governance Based on Maqashid Sharia: A Conceptual Review for a Fair Digital Economy

  • Agus Wahyudi Universitas Islam Negeri Sunan Kudus

Abstract

This study examines the integration of Maqashid Syariah principles in artificial intelligence (AI) governance in the Islamic economy sector through a systematic literature review and conceptual analysis. Along with the acceleration of digital transformation, AI presents significant opportunities to improve efficiency and innovation in Islamic finance and the halal industry. However, these technological advances also raise critical ethical challenges related to transparency, accountability, and algorithmic bias that require careful consideration from a Sharia perspective. In order to provide a thorough governance framework that harmonizes AI applications with Islamic ethical standards, this study integrates a rigorous approach to literature review with a qualitative strategy.  The results show that using Maqashid Sharia principles—more especially, the preservation of life (hifzh al-nafs), reason (hifzh al-aql), and riches (hifzh al-mal) can enhance the moral use of AI while promoting sustainable development objectives. This study proposes a four-layer governance model that includes philosophical foundations, operational principles, implementation mechanisms, and outcome measurement. However, challenges such as algorithmic bias, limited digital-Shariah literacy, and regulatory gaps must be addressed. This research provides strategic insights for policymakers, Islamic financial institutions, and technology developers to strengthen Indonesia's position as a center for ethical and sustainable Islamic digital economy

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Published
2025-12-01
How to Cite
Wahyudi, A. (2025). Building a Framework for Artificial Intelligence Governance Based on Maqashid Sharia: A Conceptual Review for a Fair Digital Economy. Annual International Conference on Islamic Economics and Business (AICIEB), 5(-), 132-138. https://doi.org/https://doi.org/10.18326/aicieb.v5i-.769