This session walks attendees through using generative AI in actuarial work directly. First we will introduce generative AI methods to create synthetic healthcare data and share some preliminary results. Second, we will walk through a case study in using generative AI as a prediction tool for a common actuarial problem. This will include how to do it, and to compare to current state of the art prediction models. The session will be practical in nature, describing how to use the models and sharing outcomes relative to other ML algorithms for problems such as predicting future health care cost or mortality. The goal is for attendees to walk away from the session with enough familiarity and background to be able to identify problem areas in their own work. These tools may be relevant and have enough familiarity for attendees to understand where to start and engage with them.