Assisted reproductive technologies offer unprecedented opportunities for family building. The fertility sector has leveraged technology both in the clinic and embryology lab to change not only the options for fertility and reproductive healthcare but also the success rates. The application of well-trained artificial intelligence (AI) tools holds further promise that care will be elevated to an even higher plane to improve outcomes and reduce costs. Simply put, the current landscape open to fertility patients is dramatically different and significantly improved from even the recent past, except in one important issue: access for underserved and underinsured populations. This lack of access has the side effect of altering the databases on which the AI tools are trained and validated and draws possible bias into the predictions. This chapter reviews issues of equity and racial disparities in healthcare within the context of tech applications and specifically how these relate to care in the fertility space. The emergence of data bias in AI training that could negatively impact the goals of fertility care is reviewed.