Modern fertility treatment is undergoing a quiet technological revolution, moving from traditional microscopic evaluation to data-driven precision, according to a fertility expert. In an interview with HT Lifestyle, she explained how the integration of artificial intelligence is fundamentally shifting how clinics approach the most delicate stages of in-vitro fertilisation (IVF). Also read | Kriti Sanon froze her eggs: IVF specialists explain all about egg freezing if you want to do it too
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“Every year, couples walk into fertility clinics carrying more than medical files,” Dr Manika Khanna, MD and chairperson of Gaudium IVF, said. “They carry years of hope. IVF has moved from a last resort to a mainstream path to parenthood, and the technology behind it has kept pace,” she added.
As clinics adopt these advanced tools, the central question for patients remains clear. Dr Khanna shared, “The question most patients ask, in different words, is a simple one, ‘Can a machine improve the chances of having a baby?'”
While AI excels at processing vast amounts of imaging data to spot patterns invisible to the human eye, Dr Khanna highlighted that the technology remains a supportive asset. According to her, the final, critical clinical decisions — and the essential emotional support required throughout the fertility journey — remain firmly outside of what the algorithm can do.
Note to readers: This article is for informational purposes only and not a substitute for professional medical advice. Always seek the advice of your doctor with any questions about a medical condition.
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Historically, selecting the right sperm for Intracytoplasmic sperm injection (ICSI) has been a highly subjective task, she shared. “Selecting the right sperm for ICSI has always depended on one embryologist looking through a microscope, grading shape and movement by eye,” Dr Khanna explained. “AI tools act as an assistant to the embryologists in this process,” she added.
⦿ Higher embryo utilisation: A 2025 pilot study published in Human Reproduction revealed that AI-assisted selection achieved an embryo utilization rate of 60.4 percent, compared to just 45.5 percent using conventional manual selection. This statistical gap translates to roughly one additional usable embryo per cycle.
Once fertilisation occurs, the challenge shifts to choosing which embryo gives patients the highest chance of a successful pregnancy.
“Embryo selection is a crucial step in IVF because not all embryos have the same potential to implant and develop into a healthy pregnancy,” said Dr Khanna, adding, “Embryologists evaluate embryos based on their morphological and developmental characteristics to identify those with the highest likelihood of success.”
While these decisions have traditionally relied on clinical experience, Dr Khanna explained that AI adds an extra layer of computational validation. “While this assessment is guided by established clinical criteria and extensive expertise, AI can provide an additional layer of objective analysis,” she said.
Clinics are increasingly relying on Erica (Embryo ranking intelligent classification assistant) to bring standardised data to the lab, Dr Khanna shared and described Erica as ‘an advanced AI-powered tool designed to support embryologists in embryo selection’.
“By analysing static images of blastocysts based on key morphological and developmental characteristics, Erica provides an objective, data-driven ranking of embryos,” Dr Khanna stated.
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She shared that the tool is meant to enhance, rather than replace, human touchpoints: “Used alongside the embryologist’s clinical judgement, it complements expert assessment, promotes greater consistency in embryo evaluation, and supports informed decision-making during embryo selection.”
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According to Dr Khanna, the data points to a clear middle ground between human expertise and automation: “The answer is that AI can improve outcomes at specific moments in the process, though it does not run the process on its own.”
One of the frontline technologies leading this charge is SiD (sperm identification device), Dr Khanna said. She described it as ‘an AI-powered system that analyses multiple sperm movement parameters to optimise sperm selection during fertility treatment, helping identify the most viable sperm for fertilisation and enhancing the potential for better-quality blastocyst formation’.
According to her, the clinical numbers backing this technological shift are stark:
⦿ 96 per cent accuracy: A 2025 model built by researchers at Hong Kong University identifies fertilisation-competent cells with over 96 percent accuracy — a distinction standard microscopes struggle to make.
