Can artificial intelligence choose the best embryo? How technology is changing IVF without replacing embryologists
Artificial intelligence is entering IVF labs to analyze images of embryos and their development patterns, but experts say the technology is best viewed as a decision-support tool, not a replacement for embryologists or a guarantee of pregnancy.
For couples undergoing IVF, the most crucial moment in the lab can boil down to a deceptively simple question: Which embryo should be transferred? What looks like a microscopic image on a screen can hold enormous emotional and clinical significance.
Artificial intelligence is now entering this decision-making process. By analyzing images of embryos, time-lapse videos, and developmental patterns, AI systems can identify features that would be difficult to evaluate consistently with the human eye and provide embryologists with an additional layer of information.
But the technology comes with an important caveat: AI cannot universally identify the “perfect embryo,” and an algorithm cannot guarantee embryo implantation or a successful pregnancy.
The American Society for Reproductive Medicine (ASRM), in its 2026 Committee Opinion on Artificial Intelligence in IVF Laboratories, describes this technology as a potentially valuable adjuvant but emphasizes that its clinical utility still requires rigorous validation. Randomized trials have not yet demonstrated that AI-assisted embryo selection improves pregnancy outcomes compared to traditional morphology-based evaluation.
AI can see patterns, but embryologists make the decisions
Artificial intelligence is finding an increasing role in IVF laboratories, especially in embryo assessment and selection, says Dr. Nidhi Sehrawit, MBBS, MS Obstetrics and Gynecology (OBGY).
More of health“By analyzing images of embryos and their patterns of development, AI-based tools can identify precise features that may support embryologists in making more consistent and data-informed assessments,” she explains.
The distinction is important. AI does not replace the broader process by which a fetus is evaluated.
Embryologists take into account morphology, developmental progress and laboratory conditions, along with their professional experience and clinical judgment. AI can add another perspective to this assessment rather than independently deciding which embryo to transfer.
This is particularly important because selecting embryos is not simply a matter of assigning an image score. Embryos develop dynamically, and time-lapse imaging can capture changes such as cell divisions and other developmental features that may not be evident from a single still image. ASRM notes that AI models can improve standardization and efficiency in embryo classification, but their ability to improve clinical outcomes remains insufficiently proven.
The evidence is promising, but not conclusive
Research on AI-assisted embryo selection has yielded encouraging results, but the results are not uniform.
A large multicenter randomized trial published in Nature Medicine compared deep learning-assisted embryo selection with standard shape-based assessment across 14 IVF clinics in Australia and Europe. Among 1,066 patients, the clinical pregnancy rate was 46.5% in the AI group compared with 48.2% in the conventional evaluation group. The study was unable to demonstrate that the AI was noninferior to standard morphological assessment of clinical pregnancy.
This does not mean that artificial intelligence has no value.
One of its immediate advantages may be consistency and efficiency. ASRM notes that classification of embryos can vary between embryologists, while AI systems can apply the same analytical framework repeatedly. In one randomized trial cited by ASRM, an AI model significantly reduced the time needed to evaluate blastocysts in a time-lapse imaging system.
The 2025 Diagnostic Systematic Review and Meta-Analysis also found that AI-based embryo evaluation showed promising diagnostic performance for implantation prediction, although the evidence should not be interpreted as evidence that AI ensures better IVF outcomes.
Why is “AI vs. embryologist” the wrong question?
The debate over artificial intelligence in IVF is sometimes framed as a competition between machines and medical professionals. In practical terms, a more realistic future would likely involve working together.
“Embryo selection is a complex process that involves much more than just analyzing an image or getting a result,” says Dr. Sahrawit. “AI can serve as an additional layer of information, offering another perspective while keeping professional judgment at the heart of the process.”
This human role becomes especially important when the AI system encounters situations that differ from the data it was trained on. ASRM cautioned that differences between patient populations, IVF clinics, laboratory protocols, and datasets can impact how reliably algorithms perform in real-world settings. The community has therefore called for prospective validation, including randomized controlled trials.
Could robots eventually run IVF labs?
The role of AI could also extend beyond evaluating embryos.
As IVF laboratories become increasingly automated, robots and computer-assisted systems may assist with repetitive, highly precise, or standardized tasks. AI is already being explored in areas including embryo grading, laboratory logistics, viewing and storage management, while automation is also being investigated in procedures such as intracytoplasmic sperm injection and sperm selection.
But complete replacement of embryologists remains unlikely.
IVF laboratories require not only technical precision, but also quality control, troubleshooting, interpretation, accountability, and decision-making in situations where an automated system may not have sufficient context.
“The same principle applies to automation and robotics,” says Dr. Sahrawit. “IVF requires not only technical precision, but also expertise, judgment, quality control and accountability at every stage of the laboratory process.”
The future of artificial insemination may be collaboration between humans and artificial intelligence
The transformation taking place within IVF laboratories is therefore less about machines taking over and more about technology that augments human expertise.
Artificial intelligence can process vast amounts of images and developmental data, identify patterns and potentially make the evaluation of embryos more consistent. Embryologists bring something that algorithms cannot independently replicate: professional judgment, laboratory expertise, and responsibility for interpreting information in the context of an individual patient’s treatment.
“So the future of IVF is unlikely to revolve around humans versus machines,” Dr. Sahrawit says. “Instead, it will be about combining the analytical capabilities of the technology with the experience and judgment of trained embryologists.”
For patients, this distinction is important. AI may eventually make parts of IVF more standardized, data-driven, and efficient. But a high-tech IVF laboratory does not mean a guaranteed pregnancy.
Technology is evolving rapidly, but the evidence is still catching up. Right now, the most credible role for AI is not as the final decision maker, but as another sophisticated tool in the hands of the people responsible for making that decision.
