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There is critically unmet need for consistently providing long-term survival with minimal treatment toxicity for AML patients. Advances in artificial intelligence\/machine learning (AI\/ML) offer new approaches to addressing clinical challenges in AML. Methods: In this systematic narrative review, 426 publications focusing on the intersection of AML and AI\/ML between January 1, 2010, and July 30, 2024, are reviewed. Results: The evolution of AI\/ML tools over time is described from a clinically relevant perspective with a distinction between early epochs of AI\/ML versus more contemporary algorithms, such as generative adversarial networks and transformer-based algorithms. This review highlights the utilization of contemporary AI\/ML algorithms via addressing diagnostic challenges, molecular risk stratification problems, and clinical outcome prediction in the context of AML. 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