Women have been underrepresented in medical research in the past; this, in conjunction with implicit biases women receive, can lead to a decrease in the standard of care. Artificial intelligence (AI) systems have the potential to aid in creating fairer healthcare for women. However, there is still a need to give more definition to the problem to fully understand when women are biased against unfairly and, conversely when sex is a factor for a good reason. 15 semi-structured interviews were conducted with healthcare practitioners to gather their perceptions on women’s healthcare. A semantic thematic analysis of these interviews yielded the following themes: Gender Influencing Health, Pregnancy, Social Factors, General Health, Treatment, Research and Training. These themes highlight that context is key to understanding the biases in women’s health and that this context is critical when developing AI models for healthcare.