Over the past years, the assisted reproductive technologies (ARTs) have been accompanied by constant innovations. For instance, intracytoplasmic sperm injection (ICSI), time-lapse monitoring of the embryonic morphokinetics, and PGS are innovative techniques that increased the success of the ART. In the same trend, the use of artificial intelligence (AI) techniques is being intensively researched whether in the embryo or spermatozoa selection. Despite several studies already published, the use of AI within assisted reproduction clinics is not yet a reality. This is largely due to the different AI techniques that are being proposed to be used in the daily routine of the clinics, which causes some uncertainty in their use. To shed light on this complex scenario, this review briefly describes some of the most frequently used AI algorithms, their functionalities, and their potential use. Several databases were analyzed in search of articles where applied artificial intelligence algorithms were used on reproductive data. Our focus was on the classification of embryonic cells and semen samples. Of a total of 124 articles analyzed, 32 were selected for this review. From the proposed algorithms, most have achieved a satisfactory precision, demonstrating the potential of a wide range of AI techniques. However, the evaluation of these studies suggests the need for more standardized research to validate the proposed models and their algorithms. Routine use of AI in assisted reproduction clinics is just a matter of time. However, the choice of AI technique to be used is supported by a better understanding of the principles subjacent to each technique, that is, its robustness, pros, and cons. We provide some current (although incipient) and potential uses of AI on the clinic routine, discussing how accurate and friendly it could be. Finally, we propose some standards for AI research on the selection of the embryo to be transferred and other future hints. For us, the imminence of its use is evident, providing a revolutionary milestone that will impact the ART.

在过去的几年里，辅助生殖技术（ARTs）一直伴随着不断的创新。例如，胞浆内单精子注射 (ICSI)、胚胎形态动力学的延时监测和 PGS 是提高 ART 成功率的创新技术。在同一趋势下，人工智能 (AI) 技术的使用正在深入研究，无论是在胚胎还是精子选择中。尽管已经发表了几项研究，但在辅助生殖诊所中使用人工智能尚未成为现实。这主要是由于建议在诊所的日常工作中使用不同的 AI 技术，这导致它们的使用存在一些不确定性。为了阐明这个复杂的场景，这篇评论简要描述了一些最常用的 AI 算法，它们的功能和潜在用途。分析了几个数据库以搜索在生殖数据上使用应用人工智能算法的文章。我们的重点是胚胎细胞和精液样本的分类。在分析的总共 124 篇文章中，32 篇被选为本综述。从提出的算法来看，大多数都达到了令人满意的精度，展示了广泛的人工智能技术的潜力。然而，对这些研究的评估表明需要进行更标准化的研究来验证所提出的模型及其算法。在辅助生殖诊所中常规使用人工智能只是时间问题。但是，选择要使用的 AI 技术需要更好地理解每种技术的相关原理，即其稳健性、优缺点。我们提供了人工智能在临床常规中的一些当前（尽管处于初期）和潜在用途，讨论它的准确性和友好性。最后，我们提出了一些人工智能研究的标准，比如选择移植胚胎等未来提示。对我们来说，它的使用迫在眉睫，这是一个革命性的里程碑，它将影响 ART。