In recent years, the integration of artificial intelligence (AI) into medicine has expanded rapidly, particularly within assisted reproductive technologies (ART) and in vitro fertilization (IVF). Traditional assessments in IVF—especially embryo morphology—are prone to subjectivity and may vary according to embryologist experience. AI-supported systems help overcome these limitations by enabling faster, more objective, and more consistent evaluation of clinical data and microscopic images. AI applications have been incorporated into multiple steps of the ART process, including oocyte and sperm assessment, fertilization analysis, embryo evaluation, ploidy prediction, and embryo selection for transfer. Beyond laboratory assessment, AI also contributes to micromanipulation, quality management, the processing of large datasets to support personalized treatment protocols, and improved genetic testing approaches. Collectively, these innovations enhance diagnostic accuracy, promote standardization, and increase treatment success rates in ART. This narrative review provides a comprehensive and up-to-date overview of AI applications within ART, with a particular focus on IVF laboratory processes, clinical decision-support tools, and related ethical considerations. A focused literature search was conducted in PubMed using the keywords “artificial intelligence” and “assisted reproduction.” The search covered the period from January 1, 2020, to May 31, 2025, and included only English- and Turkish-language publications. Eligible studies consisted of meta-analyses, systematic reviews, narrative reviews, and original research evaluating the use of AI in human ART or IVF. Conference abstracts, editorials, expert opinions, letters to the editor, case reports lacking methodological clarity, non-human studies, and purely technical computer science papers without clinical relevance were excluded. Reference lists of the included articles were also examined to identify additional sources.