Artificial Intelligence for Environmental Resilience and Sustainable Innovation

Sri  Poedji Lestari; Rosa  Lesmana; Sabil Maulana  Fauzi; Alexander Johnson Johnson

doi:10.68012/air.v1i2.239

Authors

Sri Poedji Lestari Bung Karno University Author https://orcid.org/0000-0002-3176-413X
Rosa Lesmana Pamulang University Author https://orcid.org/0009-0002-5308-6023
Sabil Maulana Fauzi Universitas Raharja Author https://orcid.org/0009-0003-1833-1027
Alexander Johnson Johnson Rey Incorporation Author

DOI:

https://doi.org/10.68012/air.v1i2.239

Keywords:

Artificial Intelligence, Environmental Resilience, Sustainable Innovation, Environmental Sustainability, Climate Adaptation

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.

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