When it comes to AI in the humanitarian sector the focus of the debate goes into the ethics of using AI, the risks of automation, of the wrong usage of data, among other topics, but it hardly focuses on how we can use machines to help us with language. Natural language processing (NLP) is the branch of artificial intelligence in charge of understanding text and spoken words the same way human beings can. As a humanitarian community, we have our language and ways of understanding the contexts and classifying them very specific to our metier. How is it then that AI ,and especially NLP, can support the humanitarian sector and how is it being used currently? What are the benefits and risks of using such a technology in our work? Can we debunk some fears and look into ethical ways of usage of such a technology? This session will bring together NLP leaders in the sector and academia to showcase some practical examples of using NLP. The discussion will be centered on the collaborations/synergies among actors and the way forward for using these technologies. At the end of the session there will be a showcase of the HumBert (Humanitarian Bert) a XLM-Roberta model, the first language model adapted on humanitarian topics and HumSet a novel and rich multilingual dataset of humanitarian response documents annotated by experts in the humanitarian response community, developed by DFS for the DEEP.