Purpose: The purpose of this review is to provide an up-to-date overview of the utility of artificial intelligence (AI) in evaluating prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scans for prostate cancer (PCa). Methods: A literature review was conducted on the Medline, Embase, Web of Science, and IEEE Xplore databases. The search focused on studies that utilises AI to evaluate PSMA PET scans. Original English language studies published from inception to October 2024 were included, while case reports, series, commentaries, and conference proceedings were excluded. In total, 13 papers were included. Five studies developed AI models for detecting distance metastasis and lymph node involvement, whilst eight studies developed AI models to detect intraprostatic cancer. Results: AI applications show promise in automating the detection of metastatic disease and anatomical segmentation in PSMA PET scans. AI was also able to predict response to PSMA-based theranostics and aids in tumour burden segmentation, improving radiotherapy planning. AI could also differentiate intraprostatic PCa with higher histological grade and predict extra-prostatic extension. Conclusion: AI has potential in evaluating PSMA PET scans for PCa, particularly in detecting metastasis, measuring tumour burden, detecting high grade intraprostatic cancer, and predicting treatment outcomes. Larger multi-centre prospective are necessary to validate and enhance the generalisability of these AI models.