Fluorescence lifetime imaging (FLI) offers several advantages, including the quantitative imaging of unique biosignatures in biological tissues, studies of drug-target interactions, and tumor margin identification. However, its adoption in surgical environments has been hindered by the time-consuming data acquisition and processing pipeline. In this work, we present an AI-enhanced rapid lifetime determination (RLD) method utilizing the SwissSPAD3 (SS3) detector, capable of acquiring a single frame to generate a large area FLI map. This method has been validated using fluorescence inclusions in tissue-mimicking phantoms, paving the way for complex in-vivo imaging. In conclusion, the AI-enhanced single-shot fluorescence lifetime estimation using the SwissSPAD3 detector represents a significant advancement in the RLD method, with promising potential for fluorescence-guided surgical applications.