Artificial intelligence for climate resilience: advancing sustainable goals in SDGs 11 and 13 and its relationship to pandemics

The integration of artificial intelligence (AI) into environmental monitoring, climate action, and sustainability has become increasingly important, particularly in tackling the global challenges associated with climate change. In this article, we critically assess the role of AI within the frameworks of the United Nations’ Sustainable Development Goals (SDGs) 11 (Sustainable Cities and Communities) and 13 (Climate Action). This study shows how AI applications can significantly enhance climate resilience and promote sustainable urban development. AI technologies enable extensive data collection and analysis through various methods, including remote sensing and sensor networks, which improve assessments of air and water quality, land use changes, and biodiversity monitoring. Another significant advantage of AI is its ability to optimize energy consumption across various sectors, leading to substantial reductions in greenhouse gas emissions. Additionally, we demonstrate that AI enhances waste management strategies by identifying recycling opportunities and streamlining logistics, ultimately contributing to waste reduction and fostering a circular economy. In the fields of agriculture and forestry, AI systems have proven effective in improving crop management and pest control practices, mitigating environmental impacts while increasing food productivity. Furthermore, AI plays a vital role in wildlife conservation efforts by assisting in tracking endangered species and analyzing satellite imagery to combat illegal activities. We also illustrate how AI supports the development of predictive climate models, enabling policymakers to create science-based strategies for effectively navigating extreme weather and climate risks, thereby fostering resilient infrastructure decisions. While the transformative potential of AI in climate initiatives is clear, we address several limitations and ethical challenges associated with its application, including concerns about data quality and accessibility, biases in AI algorithms, and the need for transparency in AI-driven decision-making. These challenges emphasize the importance of interdisciplinary collaboration and robust engagement strategies to ensure that AI applications promote equitable access to solutions for marginalized populations affected by climate change. Moreover, we examine how the COVID-19 pandemic has reshaped the landscape of AI for sustainable development, revealing both challenges and opportunities in implementing AI technologies. The pandemic has led to increased investment in remote monitoring technologies while highlighting the need for collaborative approaches to address the complex interdependencies between public health and climate resilience. Through a synthesis of relevant literature and case studies, we advocate for a holistic and collaborative approach to utilizing AI technologies in environmental management to achieve the SDGs successfully. By fostering innovation and inclusivity in decision-making processes, society can leverage AI's potential to create a sustainable and resilient future, thus advancing comprehensive climate action in alignment with the United Nations’ mission.