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These include variability in interpretation and the labour\u2010intensive nature of manual screening processes. The advent of artificial intelligence (AI) technologies, especially machine learning and deep learning, heralds a new era in cytology, offering enhanced accuracy, consistency, and efficiency. These advancements promise to mitigate traditional limitations by automating routine analyses, aiding early cancer detection, and reducing the workload of laboratory personnel. This review thoroughly examines the current status of commercial AI software in gynaecologic cytology screening. We critically assess the capabilities, performance, and impact of these AI tools in a clinical context. Additionally, the review addresses the integration challenges and potential of AI in clinical practice, including workflow integration, regulatory compliance, and ethical considerations. 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