This chapter outlines the promising integration of artificial intelligence (AI) techniques into assisted reproductive technology (ART) treatments, emphasizing its potential to optimize treatment outcomes and workflow. The first part of the chapter will delve into the current literature surrounding clinical nodal points that could benefit from AI support in decision-making processes mostly in personalized ovarian stimulation such as outcome prediction, initial dosage and trigger timing, workload balancing, and ovulation prediction. By leveraging AI’s capabilities in data analysis and pattern recognition, healthcare providers can make more informed decisions, ultimately leading to better patient outcomes. In the second part of the chapter, the focus shifts to the role of AI in supporting laboratory operations and embryologists. This involves tasks such as gamete selection and prediction of embryo viability and implantation. By incorporating AI into these processes, healthcare facilities can improve efficiency and accuracy, leading to better overall outcomes for patients undergoing ART treatments. Overall, the chapter underscores the potential of AI to complement existing medical expertise in ART treatments, offering opportunities to enhance success rates, patient satisfaction, and operational efficiency within healthcare facilities. However, it emphasizes the importance of thorough validation to ensure the reliability and accuracy of AI models before their widespread implementation in clinical practice.