While the growing interest in artificial intelligence (AI) is evident, it can sometimes be difficult to precisely identify the scope, tools, and methods underlying the concept of "artificial intelligence." This knowledge synthesis focused on the applications of AI methods in environmental health (EH), based on the literature and interviews with subject matter experts, has shed light on a new universe of terms and expressions that need to be defined, given the multitude of interpretations. AI is utilized in the field of environmental health at various stages of studies: from data collection to analysis and prediction. AI’s capabilities for processing big data offer interesting possibilities for facilitating the use of Earth observation data, simulating exposure data, highlighting regional profiles, cross-referencing environmental and health data, facilitating literature searches, and communicating results in a dynamic and tailored manner, among other things. The opportunities offered by AI in the field of environmental health are immense. However, it is essential to consider several issues before deploying this technology. These issues include legal, ethical, ecological, and technical aspects. Each of these aspects represents a source of uncertainty that must be taken into account.