A major international review published in Nature Reviews Bioengineering outlines how artificial intelligence (AI) and automation could improve IVF and reshape assisted reproductive care.
The review provides a balanced and timely perspective on how microscale engineering and AI tools are beginning to change key steps in the IVF process, including sperm preparation, oocyte handling, embryo selection and cryopreservation.
The review was led by PhD student Jennifer Lorimer from the Department of Mechanical and Aerospace Engineering at Monash University, under the supervision of Associate Professor Reza Nosrati, who has pioneered microfluidic and AI-based technologies for fertility and assisted reproduction.
The work contains clinical, ethical and implementation perspectives from Professor Robert McLachlan and Professor Deirdre Zander-Fox from Monash IVF Group, who co-fund the PhD scholarship and research, as well as critical biological insights from Professor Moira O’Bryan at the University of Melbourne.
The authors say that while assisted reproductive technologies have improved in recent decades, many IVF procedures are still manual and vary between clinics. This can affect consistency and make outcomes harder to predict.
Ms Lorimer said AI and automation could help reduce this variability by improving precision, standardising workflows and supporting clinical decisions.
“AI and automation are opening the door to a new generation of IVF technologies that are not just automated versions of manual techniques, but redesigned systems that overcome current limitations,” Ms Lorimer said.
“This shift allows us to rethink how each step in the IVF process is performed, with the goal of improving consistency and supporting better clinical outcomes.”
The review highlights the potential for future AI-enabled IVF systems to bring together real-time data across the laboratory, helping automate decision-making while accounting for biological differences between patients and samples.
“IVF involves highly delicate biological materials, including sperm, eggs and embryos, meaning that new technologies must be designed not only for speed and precision, but also for safety, reliability and clinical trust,” Associate Professor Nosrati said.
“These systems could support more objective assessment of sperm, eggs and embryos, and help embryologists make more informed decisions while keeping expert human oversight at the centre of care,” said Professor Deirdre Zander-Fox, Chief Scientific Officer of Monash IVF Group.
The authors also found that many new technologies fail to reach clinics because they do not adequately meet the biological goals of fertility procedures, while others face barriers related to cost, flexibility and integration into existing clinical workflows.
Associate Professor Nosrati said collaboration between engineers and embryologists is essential.
“The opportunity is not just to automate existing workflows, but to redesign them to better reflect the complexity of reproductive biology. Working closely with embryologists allows us to build systems that are safer, more adaptive and better aligned with clinical practice,” Associate Professor Nosrati said.
The authors say further work is needed to clinically validate these systems, improve data integration and ensure responsible translation into practice, with careful attention to patient diversity, data quality, explainability, regulation and ethics. They stress AI and automation should support, not replace, the expertise of embryologists and fertility specialists.
Read the research paper: https://doi.org/10.1038/s44222-026-00454-2
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