The Future of IVF: How AI (Artificial Intelligence) is Revolutionizing Fertility Treatments and Embryo Selection
Discover how AI (artificial intelligence) is transforming IVF (in vitro fertilization) and fertility treatments, enhancing embryo selection and boosting success rates in assisted reproductive technology.
If you're exploring the world of IVF, you’ve probably noticed how quickly new technologies are changing the way fertility treatments are offered. One of the biggest shifts in recent years has been the use of artificial intelligence – not just in general healthcare, but right in the heart of embryo selection.
For many women and couples trying to conceive, it’s hard to imagine that an algorithm or a data-based system could be part of something as emotional and human as fertility treatment. And yet, artificial intelligence is now helping embryologists make more precise, consistent, and informed decisions during key stages of the IVF process.
From image-based platforms like CHLOE or Life Whisperer to systems that combine genetic testing with AI, such as Magenta-AI™, these tools are transforming the way embryos are analysed, selected and transferred – with the goal of improving outcomes.
In this article, we’ll walk you through how AI is being used in IVF today – from imaging and embryo grading to deep learning models and data interpretation. You’ll discover the leading technologies used around the world, how they differ, and what they mean for your chances of success.
And most importantly: we'll explain it all in a way that makes sense – no medical degree required.
Let’s take a closer look at how artificial intelligence is shaping the future of IVF and what this could mean for your journey.
Understanding artificial intelligence in IVF treatment
As new technologies become part of modern reproductive medicine, artificial intelligence is quickly emerging as one of the most exciting tools in the IVF world. But what exactly does AI mean in this context – and how can it support your fertility journey?
Whether you’re just starting to explore IVF or you’re already planning a treatment abroad, understanding the role of AI can help you ask the right questions and feel more confident in your choices.
What is AI and how is it used in reproductive medicine?
Artificial intelligence refers to the use of computer systems that are able to analyse data, recognise patterns and make decisions – often faster and more accurately than a human could. In IVF, AI is used to evaluate embryos, eggs, sperm and lab performance by processing enormous amounts of information that would otherwise take hours to assess.
The goal is not to replace embryologists, but to support them in selecting the embryos with the highest chance of success – based on consistent, data-driven evaluations. Some AI tools analyse images of developing embryos, others interpret genetic results, and some do both.
You might hear terms like machine learning, deep learning, or AI models – these all describe different types of artificial intelligence that can be used during fertility treatment. What they have in common is their ability to improve accuracy and reduce guesswork during the IVF process.
The role of AI in IVF laboratories and decision-making
Inside the IVF laboratory, precision matters. Even the smallest differences in embryo development can affect the outcome of a treatment. That’s why more and more fertility clinics are turning to AI-based technologies: they offer an additional level of objectivity in moments when important choices need to be made.
In many labs, time-lapse incubators are already used to monitor embryo development. AI systems can analyse these images frame by frame and flag subtle patterns that may indicate higher embryo viability. Others focus on sperm selection or oocyte quality – especially in cases involving egg donation or patients over 35.
By using AI to support these decisions, clinics aim to increase the success rate of IVF and offer patients more personalised treatment options. For you, this means that your IVF cycle may benefit from advanced tools that are not always visible – but can make a real difference behind the scenes.
The benefits of AI in embryo and egg evaluation
Choosing the right embryo is one of the most important – and delicate – steps in the IVF process. It’s also one of the most emotionally charged moments for patients. For years, this decision was based mainly on the visual judgment and experience of embryologists. But with the introduction of artificial intelligence, this process is evolving.
AI now supports clinics in making embryo and egg selection more consistent, transparent and data-based. While no technology can guarantee success, using AI can help reduce the number of failed transfers and shorten the overall treatment journey.
How machine learning supports embryologists in IVF
Machine learning models are trained on thousands of data points from previous IVF cycles. They learn to detect patterns in embryo development that have been associated with higher implantation rates, better clinical outcomes and healthier pregnancies.
For example, AI can assess whether an embryo divides in time, if the shape and movement appear normal, or if the embryo’s internal structure suggests a high level of viability. These evaluations can take place within a few seconds and are based on a consistent set of criteria – not personal interpretation alone.
This doesn’t mean embryologists are replaced – quite the opposite. They work alongside AI systems to confirm findings and combine medical insight with data. Together, this human-and-machine collaboration improves both speed and precision.
The advantages of using deep learning in reproductive care
One area where AI shines is in image analysis. Deep learning – a subset of machine learning – is particularly good at reading complex visual data, such as time-lapse images of embryo development.
In practical terms, this means AI can look at subtle signs that may not be obvious to the human eye. For example, it might detect unusual changes in cell division timing, or highlight embryos that follow ideal developmental patterns.
This kind of imaging analysis can be especially helpful for patients who have experienced multiple failed IVF cycles or are trying to avoid another disappointment. With additional insights from AI, clinics can focus more confidently on embryos with the highest chance of success.
CHLOE by Fairtility: a leading AI technology in IVF labs
One of the best-known AI tools currently used in IVF laboratories around the world is CHLOE – an advanced artificial intelligence platform developed by Fairtility. CHLOE supports clinics in evaluating the quality of both embryos and eggs, offering a new level of precision and consistency in IVF decision-making.
Unlike systems focused on a single data source, CHLOE is a full platform with different modules – each designed to address a specific part of the IVF process. These tools are used not only to assist in embryo selection through artificial intelligence but also to support clinic-wide quality and performance.
The role of CHLOE EQ, OQ and KPI in AI-powered IVF
CHLOE consists of three main modules:
CHLOE EQ (Embryo Quality): This module analyses time-lapse videos of embryo development to support the selection of embryos with the highest implantation potential.
CHLOE OQ (Oocyte Quality): This part focuses on egg assessment – which can be particularly important in cases involving egg donation or women over 35.
CHLOE KPI (Key Performance Indicators): This module helps clinics evaluate their lab processes and consistency across IVF cycles.
Together, these tools help embryologists make more informed decisions and allow clinics to implement AI technologies in a practical, patient-focused way. CHLOE is not about replacing lab expertise – it’s about offering a second, data-driven opinion that helps refine treatment planning and improve IVF outcomes.
Global implementation of AI in IVF through CHLOE
CHLOE is already being used in IVF laboratories across Europe, North America, Latin America, and Asia. As a cloud-based system, it can be integrated into different lab environments – especially those already using time-lapse incubators.
Because CHLOE has been trained on thousands of anonymised cases from diverse clinical settings, it continues to evolve and adapt. This wide-ranging experience means its predictions become more accurate over time, and its feedback more relevant to different patient profiles.
For patients like you, this means there’s a growing chance your chosen clinic may already be using CHLOE behind the scenes – helping to identify the embryo or egg that gives you the best possible chance.
Life Whisperer: deep learning for embryo selection
Another major player in the world of AI-supported IVF is Life Whisperer, a technology developed in Australia that uses deep learning to support embryo selection based on image analysis. Unlike systems that rely on time-lapse video, Life Whisperer evaluates static images of embryos to estimate their viability.
Its goal is simple: help embryologists make faster and more consistent decisions by using artificial intelligence to predict which embryos are most likely to implant successfully.
How image-based AI technologies are used in IVF treatment
Life Whisperer uses AI algorithms trained on thousands of embryo images, each linked to known clinical outcomes. Based on this data, the system learns to detect visual features that correlate with successful implantation and healthy pregnancies. This includes subtle differences in shape, symmetry, and structure that may not be visible to the naked eye.
One of the advantages of this method is that it works with standard microscope images – no special equipment or time-lapse system is required. That makes it accessible for many IVF clinics worldwide, including those that don’t use advanced incubators.
For patients, this means AI can be part of the process even if your clinic isn’t using complex hardware. The technology runs in the background and supports the embryologists during embryo grading – an important step before transfer.
Where Life Whisperer is implemented and what makes it unique
Life Whisperer is now used in clinics across multiple continents, and its AI model continues to improve as more data is collected. Because it’s based on cloud software, updates and improvements can be rolled out regularly without needing to change lab routines.
What makes Life Whisperer particularly interesting is its ease of integration. Clinics can upload images and receive a viability score within minutes – helping them decide which embryo to prioritise for transfer, especially in cases where several embryos appear similar.
While it doesn’t replace clinical expertise or genetic testing, Life Whisperer adds an extra layer of confidence – and can be a valuable tool in clinics that aim to improve IVF success without significantly changing their workflow.
iDAScore and EmbryoScope+: AI and time-lapse in modern IVF
In many IVF clinics, embryos are already observed using time-lapse incubators – systems that take detailed images of embryo development without disturbing the culture environment. One of the most widely used combinations of AI and time-lapse imaging is the duo of iDAScore and EmbryoScope+, both developed by the company Vitrolife.
These tools allow embryologists to monitor embryos continuously and apply AI-supported scoring systems to help guide embryo selection.
Machine learning meets morphokinetics in embryo evaluation
iDAScore uses machine learning to evaluate the morphokinetic development of embryos – meaning it tracks how and when key stages of cell division occur. The system compares these developmental timelines with thousands of past IVF cycles to assess which embryos have the highest predicted viability.
Unlike traditional grading systems that rely on a visual snapshot at a single moment in time, iDAScore benefits from a full timeline of embryo development. It assigns a score to each embryo, offering an additional reference point for the embryologist when planning embryo transfer.
The result is a more consistent and data-driven approach to embryo grading, especially in clinics that already use EmbryoScope+ for their routine monitoring.
Benefits of AI in IVF: real-world application of iDAScore
What makes iDAScore valuable is its ability to reduce human subjectivity while still giving the embryologist full control. The AI offers a suggested ranking based on historical data and pattern recognition, but final decisions remain in the hands of the medical team.
This blend of AI and human expertise is especially helpful when multiple embryos appear similar under traditional grading. By offering a second opinion based on validated clinical data, iDAScore can help narrow down the best candidates for transfer.
For patients, this means a more transparent selection process and potentially higher success rates, as decisions are informed by both experience and technology.
" Artificial intelligence doesn't replace human care – it enhances every decision on your path to becoming a parent."
Magenta-AI™ with PGT-A+: combining artificial intelligence and genetics
In some IVF laboratories, artificial intelligence is being used not only to analyse images but also to interpret genetic data. A key example of this approach is Magenta-AI™, a system designed to combine PGT-A+ – a type of preimplantation genetic testing – with AI-driven decision support.
This integration allows clinics to go beyond visual embryo assessment and add an extra layer of precision through genetic information. The result is a more comprehensive view of each embryo’s potential.
The use of AI to enhance genetic screening in IVF
PGT-A+ stands for an advanced version of preimplantation genetic testing for aneuploidy. It analyses the embryo’s chromosomes to identify those that have the correct number – a critical factor in embryo viability and healthy development.
Magenta-AI™ adds artificial intelligence to this process by analysing and interpreting the results of PGT-A+ with greater consistency. It acts as a smart assistant that supports embryologists and genetic specialists in identifying the embryos with the highest chance of leading to a successful pregnancy.
Rather than manually reviewing raw genetic data, the AI model processes multiple variables and highlights the embryos that meet specific criteria – helping clinics make faster, more confident decisions.
What sets Magenta-AI™ apart in embryo assessment
Magenta-AI™ is not widely available and is currently integrated within a specific lab environment. Unlike cloud-based tools, it is developed as a proprietary system and not offered as a general software service.
What makes it unique is its combination of genetic screening and artificial intelligence, which goes beyond visual or time-based assessments. It may be particularly relevant for patients with a history of infertility, recurrent miscarriage, or known genetic risks – offering another layer of reassurance during embryo selection.
As with all technologies, Magenta-AI™ is designed to support – not replace – medical judgment. It enhances the process by offering a data-driven analysis of embryo viability using both genetics and AI, contributing to improved clinical outcomes and greater transparency.
PGT-A + AI: advanced technologies in IVF laboratories
While some AI tools are well known and marketed as standalone products, others are quietly integrated into IVF laboratories, particularly in combination with genetic testing. In several countries, laboratories and genetic testing providers are developing AI-supported systems to enhance the evaluation of PGT-A results – often as internal tools rather than commercial platforms.
These solutions are designed to increase the accuracy and consistency of embryo selection by applying artificial intelligence to large datasets of chromosomal information.
The implementation of AI in IVF labs through genetic testing
Certain IVF laboratories now use AI algorithms to assist in interpreting the results of PGT-A, focusing on patterns that might indicate higher chances of implantation or lower risk of miscarriage. These applications of AI often work in the background and are not always disclosed to patients in detail.
In some cases, clinics may also combine AI-based tools for embryo imaging with PGT-A analysis to cross-check findings and prioritise embryos more precisely. This kind of integration reflects the growing trend toward precision and personalisation in fertility.
Even though these systems vary in sophistication and visibility, their goal remains the same: to improve IVF outcomes by offering a more complete view of the embryo – both visually and genetically.
Which labs integrate AI with PGT-A behind the scenes
Many of these AI models are developed in collaboration with universities, biotech companies or private research labs. Since they are not sold as public products, there’s often limited information about them available online.
However, their presence in the IVF industry is growing – particularly in clinics focused on innovation and advanced reproductive technologies. Patients may not always see these tools directly, but they may still benefit from them through more accurate embryo ranking and transfer planning.
If you're considering an IVF clinic abroad, it can be helpful to ask whether the lab uses any form of AI alongside genetic testing. Even if the answer is yes, the exact details may vary – but asking the question shows you're informed and proactive about your treatment choices.
Innovations in AI for IVF from North America and Asia
While many AI technologies in IVF are developed in Europe or Australia, some of the most cutting-edge innovations come from North America and Asia. Clinics and research centres in countries like the United States, Canada, Japan and South Korea are exploring new ways to combine AI with automation, lab robotics and advanced diagnostics – often with the goal of streamlining processes and improving IVF success rates.
These developments are shaping the next generation of fertility treatment tools and redefining what’s possible in assisted human reproduction.
Robotics and artificial intelligence in Asian IVF clinics
Japan and South Korea are known for their early adoption of technology in medicine – and IVF is no exception. In several clinics and research labs, robotics are being used to automate tasks such as sperm selection, embryo culture and even ICSI (intracytoplasmic sperm injection). Combined with AI, these systems aim to reduce human error and create more consistent conditions during the IVF procedure.
There are also promising projects focusing on AI-based assessment models that predict embryo viability based on optical light microscopy during IVF, helping embryologists make faster and more standardised decisions.
While many of these tools are still in development or limited to specialised centres, they give us a glimpse into the future of IVF – one where human expertise is supported by highly precise, AI-guided systems.
Smart planning and the role of AI in North American fertility labs
In the United States and Canada, AI is increasingly used in treatment planning, lab monitoring and prediction of embryo viability. Some clinics use AI models to suggest stimulation protocols, track lab performance over time, or even personalise treatment based on large sets of clinical data.
Research institutions and biotech startups are also working on systems that can analyse both clinical and lifestyle data to predict IVF outcomes more accurately. While these tools are still being tested, they highlight the direction in which the IVF industry is heading: more data, more precision, and more tailored care.
Although these technologies are not yet standard everywhere, they are setting new benchmarks. For patients, that means more opportunities to benefit from innovation – especially when seeking treatment in regions known for medical technology leadership.
What AI can and cannot do in IVF
With all the impressive advances in artificial intelligence, it’s easy to assume that AI might soon be able to replace human decision-making in IVF altogether. But in reality, AI is not here to take over – it’s here to support. Understanding both the benefits of AI and its limitations can help you feel more confident and grounded as you consider your options.
What AI technologies can do for your IVF journey
AI can support embryologists by analysing large amounts of visual and genetic data with incredible speed and consistency. It can detect patterns linked to embryo viability, suggest rankings based on historical success rates, and help clinics monitor their lab performance over time.
In many cases, AI tools offer a second layer of analysis – not replacing clinical judgment, but reinforcing it. This combination of human and machine input can improve the accuracy of embryo selection, especially when embryos appear similar under the microscope.
AI can also reduce human subjectivity in evaluations, making the process more transparent and reproducible across different IVF cycles.
Why human expertise still matters in every IVF decision
No matter how advanced an AI system is, it cannot replace the intuition, experience and holistic understanding that comes from years of working with real patients. AI doesn’t know your personal history, your emotional resilience, or your unique values. That’s why final decisions should always rest with the medical team – ideally in partnership with you.
AI also has limitations: it can’t predict the exact outcome of an embryo transfer, nor can it guarantee a healthy pregnancy. It works with probabilities, not certainties.
Think of AI as a compass, not a crystal ball. It points the way, but the journey still depends on many factors – including the skill of your clinic, your medical background, and sometimes just nature itself.
If you feel unsure or overwhelmed by the idea of AI in IVF, you’re not alone. What matters most is that you feel informed and supported – and that you understand how each technology plays a role in the bigger picture of your fertility care.
Choosing an IVF clinic that uses artificial intelligence
If you're curious about AI-supported IVF and wondering how to find a clinic that offers these technologies, you're not alone. More and more patients are asking about the use of AI – but many clinics don’t communicate it openly. That’s why it can be helpful to know what to look for and what questions to ask.
Questions to ask about the use of AI in IVF clinics abroad
Not every clinic that uses AI talks about it on their website. Some tools, especially those used in embryo imaging or genetic data analysis, run in the background without being part of a visible service.
To get clarity, you might ask:
Does your lab use any form of artificial intelligence in assisted reproductive technologies?
Do you work with time-lapse incubators or image-based AI platforms?
Is PGT-A combined with any form of algorithmic analysis or AI interpretation?
How do you evaluate embryo quality – is AI involved in this process?
These questions are not about choosing “the best clinic” – they’re about understanding the tools and standards used in the lab. The answers can give you insight into how modern and data-driven the clinic’s approach is.
Evaluating the implementation of AI technologies before choosing
Even if a clinic confirms they use AI, it’s worth asking how the technology is implemented. Is it used to support decision-making? Are embryologists still involved in every step? What role does the AI system play in ranking or selecting embryos?
Remember: the use of AI should always enhance – not replace – the expertise of the medical team. Clinics that value transparency and patient understanding will usually be open to explaining how their technology works and how it might affect your treatment.
If you're working with a consultant, you can also ask them which clinics have a reputation for innovation and data-driven care. You don’t need to become a tech expert – but knowing the basics puts you in a stronger position to make informed choices.
Transparency and data sources: what you should know
The field of assisted reproduction is evolving rapidly, and artificial intelligence is becoming an increasingly important part of that development. However, not all tools are publicly promoted or available in every clinic, and many technologies are still in clinical validation or early implementation.
This article is based on publicly available online sources, including scientific publications, company websites, research articles and open access platforms. While we’ve done our best to ensure the accuracy of the information presented, please note:
This is not medical advice, and it should not replace a personalised consultation with a fertility specialist or clinic.
The tools described here are used in different ways, depending on local regulations, laboratory capabilities and clinic preferences.
Not all clinics using AI will explicitly name the tools they use, and some systems may still be in testing or applied only in specific cases.
Our goal is to help you better understand the current landscape of AI in IVF – so you feel more prepared, more informed, and more empowered when making decisions about your own treatment.
If you’d like help navigating these choices, we’re here to support you.
Your next step: explore IVF options across Europe
If you're currently researching IVF clinics abroad and want a clear, trustworthy overview of what’s actually possible – legally and practically – we’ve created something to help you.
Our guide gives you a detailed summary of:
Where specific treatments like egg donation, gender selection, or single and lesbian motherhood are legally available
What options exist for women over 50
How laws differ from country to country
And what the costs and success rates look like, using one real example from Northern Cyprus
This guide will help you get oriented – without pressure, and without having to search for hours online.
Click here to get your free guide to IVF destinations in Europe
It’s the perfect first step if you’re thinking about treatment abroad, but still need clarity before moving forward.
We’re here to help you feel informed, empowered, and supported – every step of the way.
English (UK) 
Deutsch 
Français 
Italiano 
Español
0 comments