The use of Al brings the promise of the automation of many tedious and time-consuming human processes. Considering the current market demand for highly qualified medical staff, the automation of processes can bring assistance and ensure the consistent provision of services in the face of the constantly growing demand for IVF. Thanks to Al, the automation of, e.g., ovarian reserve ultrasound examinations will allow the transfer of the skills and knowledge of highly qualified medical experts into the hands of each service provider.  Al-based recommendation system for an optimal hormonal stimulation protocol based on available clinical data, including DNA polymorphisms and the relationship of specific polymorphisms with other features. The use of assisted reproductive technology (ART) by infertile couples is increasing by 5% to 10% per year. With the constantly growing demand for fertility diagnostics, we face a global challenge to increase the effectiveness of assisted reproductive techniques. Thanks to personalised recommendation systems based on Al, doctors can create the most effectual and cost-effective diagnosis and treatment paths. Shortening the treatment process on the patient's side is one of the critical challenges faced by every IVF clinic. Artificial intelligence, including predictive systems, can help shorten this process by reducing the number of attempts made per cycle. Predictive systems are able, better than humans, to predict specific processes and phenomena, such as which embryo will give rise to a healthy pregnancy.