AI may be particularly beneficial in aquatic sciences because many hydrologic processes are challenging to generalize and expensive to measure and because the biota is often cryptic and difficult to observe. New AI-based solutions that are faster, cheaper and better at uncovering complex patterns and that provide new opportunities are coming online rapidly and will likely revolutionize aquatic sciences. We describe recent examples of AI approaches including measuring and modelling stream flow, joint modeling of stream flow and temperature, tracking individual fish, and the opportunity that AI provides for integrating among and across hydrological and ecological areas of study. As it is also very important to make AI models openly available to users, we also discuss strategies for operationalizing AI models in aquatic sciences.