Breast cancer is one of the most common cancer types amongst European countries and one of the leading causes of death. While in many European countries there is already free breast cancer screening in place, many women feel uncomfortable getting screened due to concerns with discomfort and radiation exposure. New screening methods - such as thermography - have been emerging to combat this potential discomfort. Thermography relies on detecting heat and blood flow abnormalities to detect malignant tumors, but at the moment it is currently not as effective or accurate as mammography is, though the promise of AI could potentially indicate a pattern of more accurate thermography image analysis and results. The goal of this study is to use information from a multitude of women's experiences in the screening process to determine the obstacles that women face when undergoing a breast cancer screening, and then assess whether AI-coupled thermography can act as a new tool to improve the screening process. Feedback was gained in two different phases, the first being an online survey for women 18 and over to collect initial data and find people to recruit for the second phase, which involved focus groups. After completing the focus groups phase, the online survey (developed by two of the study others) was uploaded again to gain new responses from a different set of people. At the end of the survey, participants could express interest in joining a focus group, upon which a Microsoft Teams link was sent via email. Focus groups lasted for 60 mins on Microsoft Teams and were recorded. Descriptive statistical analysis was used, in the form of Cronbach's alpha to measure the test's internal consistency, as well as t-tests and cross-tabulations and frequencies. The pilot focus group consisted of 7 women, and the follow-up focus group consisted of 11 women out of 24 women who expressed interest in joining a focus group (from the 101 women who filled out the online survey). Most of the focus group participants had past experience with screening, and MRI was deemed the least comfortable method while ultrasound was deemed the most. Participants thought of screening as overall a positive initiative, but some did find mammographies painful/uncomfortable and expressed curiosity on why exposure to radiation in certain screening tools is needed. Participants cited a family history of breast cancer or a feeling of personal responsibility as the reason to get screened; barriers included being too young, feeling that breast size would be a hindrance (regardless of size), not having any problems to get screened for, and long wait times. Participants felt that interaction with clinical staff was overall a large factor that affected their perception of the screening - poor interactions could be a barrier for getting screened. Another consensus the group came to was the importance of clear explanations of the procedure and being adequately informed of what they were getting into. Thermography overall was perceived as a positive due to its minimally invasive mechanism of screening; the AI being used in tandem with it was met with neutral to positive responses, though most participants stated they would like a clearer explanation as to how AI could be incorporated into the thermography procedure. Concerns were brought up with displaying nudity in front of a camera for the procedure, long wait times due to the expensiveness and novelty of the thermography machine, the lack of full transparency regarding the technology and where the data is shared to, and the cold temperature during the procedure. Of the survey responses, 98% stated that breast cancer screening is important; the biggest barriers to screening included no recommendation from doctor/no perceived need to get screened and pain. Survey participants also emphasized the need for clear and transparent information before the screening procedure, and positive interactions with medical stuff during the procedure.