Artificial intelligence (AI) is making significant inroads into healthcare, and assisted reproduction is no exception. In recent years, numerous software platforms have emerged that analyse images and data from oocytes or embryos, and in this article, we will explain how they can contribute to decision-making in the in vitro fertilisation laboratory. An AI model serves as a ‘trained expert’ inside the computer: it learns by reviewing many real cases from the past (medical records, images, results, etc.) and extracts patterns to estimate probabilities in a new case. For example, using the patient’s age and a photo of an embryo, it can calculate the probability of achieving a pregnancy. It is not magic, nor does it predict the future: it provides estimates, not certainties.

Nowadays, it is relatively common to have friends or family members with problems in achieving pregnancy, and even we can be affected at any given time.

During ESHRE 2025, several papers were presented analysing the impact of Fast Warming techniques on previously vitrified blastocysts. This protocol consists of a shorter and more intense thawing process compared to the standard one, resulting in significantly reduced exposure times to rehydration solutions and cryoprotectants.