UAVs are nodes that can fly autonomously or can be operated remotely. The clustering of UAVs forms what is known as a FANET network. In a FANET the nodes mobility is much higher than in a MANET which results in more frequently changes in the network topology. Consequently, the broadcasting of packets are also expected to be executed more frequently which can cause redundancy, contention, and collision of packets, also known as the Broadcast Storm Problem (BSP). In this work, we propose the integration of artificial intelligence techniques to the analysis of the retransmission packets in a FANET. In this regard, various models commonly used in telecommunications networks were trained. As a result, an AI-based protocol that reduces the BSP problem is presented. Specifically, the AI-based protocol selects between two hybrid BSP reduction models. The results show that the proposal is meaningful in achieving greater efficiency in the retransmissions savings and thus in the energy consumption.