Artificial Intelligence in Climate Resilience: Evaluating Contributions to SDG 13

In recent years, there has been a significant increase in artificial intelligence (AI) approaches for Sustainable Development Goals (SDGs), particularly SDG 13: Climate Action. Several AI technologies, such as machine learning, deep learning neural networks, and big data analytics present new tactics to tackle the complex problems of climate change. Via improving decisionmaking, predicting future outputs, and effectively managing vast data, these technologies help increase the accuracy of climate forecasts, optimization of resource allocation, while enabling faster responses to climatic change impacts. Yet, numerous challenges remain despite these advances including the need for high-quality data and robust algorithms as well as addressing ethical concerns, such as privacy of information with reference to the environmental effects of AI. With the help of systematic literature review, the present study investigates emerging patterns and analyses the findings to identify how AI can improve climate resilience and support mitigation and adaptation efforts in alignment with SDG 13. It underscores the need for ongoing innovation, interdisciplinary cooperation, and constructive legislation. Evidence indicate that AI has the potential to greatly enhance climate resilience if technical and ethical issues are properly addressed.