We explore whether and to what extent using ambiguous communication can be beneficial for the sender in persuasion when the receiver is ambiguity averse. In our model, ambiguity enters only through how (and if) the sender chooses to allow the realization of some payoff- irrelevant ambiguous events to determine which statistical experiment is used to generate ac- tion recommendations for the receiver and dynamic inconsistency plays no role. An ambiguous communication strategy is a source of ambiguity together with a collection of statistical exper- iments, one for each ambiguous event. We provide a concavification characterization of the sender’s optimal ambiguous communication. The characterization highlights the necessity of using a collection of experiments that form a splitting of an experiment whose recommen- dations are incentive compatible for the receiver. At least some of the experiments in the collection must be Pareto-ranked in the sense that both the sender and receiver agree on their ranking. The existence of a binary such Pareto-ranked splitting is necessary for ambiguous communication to benefit the sender, and, if an optimal Bayesian persuasion experiment can be split in this way, this is sufficient for an ambiguity-neutral sender as well as the receiver to benefit. We show such gains are impossible when the receiver has only two actions available. Such gains persist even when the sender is ambiguity averse, as long as not too much more so than the receiver and not infinitely averse. They are also robust to the receiver being more ambiguity averse than the sender thought. An illustrative example in the context of banking regulation and stress testing is provided.