ARTIFICIAL INTELLIGENCE-BASED CLIMATE WAQF ECOSYSTEM: TRANSFORMING ABANDONED WAQF ASSETS INTO SUSTAINABLE CLIMATE FINANCING TO ACCELERATE THE SDGS: EKOSISTEM WAKAF IKLIM BERBASIS KECERDASAN BUATAN: MENTRANSFORMASI ASET WAKAF TERBENGKALAI MENJADI PEMBIAYAAN IKLIM BERKELANJUTAN UNTUK MEMPERCEPAT PENCAPAIAN SDGS

Abstract

The climate crisis and the financing deficit for the Sustainable Development Goals (SDGs) are two interrelated existential threats. The OECD (2025) notes that the SDG financing gap has surged 60% to USD 4 trillion annually, while global climate finance needs reach USD 6.4 trillion annually by 2030. Paradoxically, the world's waqf assets, estimated at USD 1 trillion annually, are largely idle and unproductive due to weak management and a lack of management technology. This study integrates Artificial Intelligence (AI) with abandoned waqf assets to create an ethical, scalable, and sustainable climate finance mechanism. Using a PRISMA protocol-based Systematic Literature Review of 50 scholarly sources (2023–2026) analyzed thematically and bibliometrically, the study identifies four critical gaps: the absence of an integrated AI–waqf–climate finance–SDGs model; the absence of a machine learning-based Social Return on Waqf Investment (SROWI) metric; The absence of an AI-based inventory system for idle waqf assets; and the lack of integration of Islamic Social Finance Theory with the Resource-Based View. In response, this study proposes the Climate Waqf Intelligence Framework (CWIF), an original four-layer conceptual framework—asset mapping (Computer Vision/GIS), climate project intelligence (ESG-SDGs-based ML), impact forecasting (Deep Learning LSTM), and SROWI measurement (NLP)—based on a synthesis of the three theories and principles of Maqasid al-Shariah. Its contributions are both theoretical and practical through policy recommendations for BWI, the Financial Services Authority (OJK), and relevant ministries.