A new AI reconstruction approach restored image quality and maintained quantitative uptake accuracy in four-fold accelerated PSMA PET imaging across different scanners and tracers. The Channel Dense Dense U-Generative Adversarial Network (Channel Dense Dense U-GAN) reportedly improved performance while preserving quantitative measures important for staging and treatment decisions. If validated across broader clinical workflows, faster acquisition with preserved quantitation can reduce scan times and improve throughput. For oncology imaging stakeholders, the immediate operational benefit is less wait time and potentially improved patient experience without sacrificing standardized SUV-based interpretation.