  In recent years, artificial intelligence (AI) has deeply impacted various
fields, including Earth system sciences. Here, AI improved weather forecasting,
model emulation, parameter estimation, and the prediction of extreme events.
However, the latter comes with specific challenges, such as developing accurate
predictors from noisy, heterogeneous and limited annotated data. This paper
reviews how AI is being used to analyze extreme events (like floods, droughts,
wildfires and heatwaves), highlighting the importance of creating accurate,
transparent, and reliable AI models. We discuss the hurdles of dealing with
limited data, integrating information in real-time, deploying models, and
making them understandable, all crucial for gaining the trust of stakeholders
and meeting regulatory needs. We provide an overview of how AI can help
identify and explain extreme events more effectively, improving disaster
response and communication. We emphasize the need for collaboration across
different fields to create AI solutions that are practical, understandable, and
trustworthy for analyzing and predicting extreme events. Such collaborative
efforts aim to enhance disaster readiness and disaster risk reduction.
