Sri Poedji Lestari
Bung Karno University

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Artificial Intelligence for Environmental Resilience and Sustainable Innovation Sri Poedji Lestari; Rosa Lesmana; Sabil Maulana Fauzi; Alexander Johnson Johnson
AI, Innovation, and Resilience for the Environment (AIR) Vol. 1 No. 2 (2026): AI, Innovation, and Resilience for the Environment (AIR) Journal
Publisher : Sinar Mentari Sundara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/air.v1i2.239

Abstract

Environmental challenges such as climate change, resource depletion, biodiversity loss, and increasing pollution require innovative and adaptive solutions to strengthen environmental resilience. Artificial intelligence (AI) has emerged as a transformative technology capable of improving environmental monitoring, prediction, and decision-making processes. This study examines the role of artificial intelligence in enhancing environmental resilience and promoting sustainable innovation across various sectors, including natural resource management, climate adaptation, waste management, environmental conservation, and smart environmental systems. This study adopts a Systematic Literature Review (SLR) methodology integrated with bibliometric analysis and thematic content analysis to identify research trends, conceptual developments, and emerging themes related to AI applications in environmental sustainability. The selected studies were analyzed using VOSviewer, Tableau, and Microsoft Excel to visualize knowledge structures, thematic relationships, and research patterns. The findings reveal that AI significantly contributes to environmental resilience by enabling advanced data analysis, early detection of environmental risks, predictive assessment, resource optimization, and evidence-based decision-making. Furthermore, AI-driven innovations support sustainable practices through renewable energy optimization, precision agriculture, waste management improvement, water resource monitoring, and smart city development. However, challenges remain regarding data quality, technological accessibility, computational requirements, ethical considerations, and responsible governance. The study concludes that AI has substantial potential to accelerate environmental resilience and sustainable innovation when supported by appropriate policies, stakeholder collaboration, and long-term sustainability strategies. By integrating intelligent technologies with responsible environmental management approaches, AI can serve as a strategic enabler in addressing complex ecological challenges and supporting a more adaptive, resilient, and sustainable future.