Key applications of AI in reproductive medicine include embryo selection, outcome prediction, individualized treatment protocols and associated interventions exist [Orovou, 2025], the relevance, or indeed value of AI in fertility nursing and midwifery care has yet to be studied fully. Cromack, 2025 and colleagues explored patients’ perceptions of AI in fertility care, however their research related to clinical interventions and not fertility nurse/midwife interactions. Interestingly, the participants in Cromack’s study favoured clinicians’ perceptions/opinions to AI prediction modelling. This suggests a lack of trust in what is currently perceived to be a relatively novel approach to fertility practice. Nevertheless, there is some concern that AI tools may be implemented fairly rapidly in clinical settings, or used by patients before they seek clinical support. This webinar allows for discussion of the implementation of AI, and focuses on its potential impact on the current role of fertility nurse specialists and midwives. The webinar profiles key areas where AI is already being applied in daily settings, focusing on the increasing demand for, and use of first-line 24-h patient-support services. Patient portals already exist as an extension to electronic patient records (EPR). These communication tools between clinics and patients permit secure patient access to their records and are designed to seamlessly share appropriate data with the patient and ‘optimize clinic/patient interaction’. Applications (‘Apps’) are being trialed across women’s health (including fertility services e.g. https://www.charliemedical.ca). These apps claim to track menstrual cycles and predict ovulation, and also claim to ‘reduce the burden’ on fertility nurses/midwives, to assist them in responding in person to frequent enquiries relating to medication dosage, timing, side effects, or the provision of general reassurance. The American Society of Reproductive Medicine produced a short video on this subject, with nurse Jennifer Wood expressing anxiety around what may become a substitute to human interaction and a barrier to the fertility nurse/midwife–patient relationship, thus detracting from the delivery of quality patient care (Fertility Support and AI: Help or Hinderance). And finally, women and couples’ transitioning from fertility to antenatal care require a sensitive approach, which requires continuity of care, and in-depth knowledge of the patient history and fertility journey. Implementation of AI-based tools has the potential to remove human interaction and reduce the value that patients have always placed on the delivery of quality fertility care through the provision of fertility nurses and midwives. It is important to discuss how nurse specialists’ and midwives’ roles need to adapt in this transition phase, as AI influences our daily lives and clinical interactions.

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