Jason, ElliottAlsloum, Nada2023-07-062023-07-062023-04-03https://hdl.handle.net/20.500.14154/68533Background Artificial intelligence (AI) refers to the ability of machines to accomplish tasks that traditionally require human intelligence. In the healthcare sector, especially in the radiology field, AI has found the optimal environment to flourish and several applications have been incorporated into daily radiology workflow. This rapid integration of AI into radiology practice could have a significant impact on key radiology professionals, namely radiologists and radiographers, especially in Saudi Arabia, which aims to be the global leader in AI by 2030 under a strategic plan known as Vision 2030. Methodology A qualitative study was conducted to explore computed tomography radiographers’ and radiologists’ experiences and perceptions regarding AI adoption into radiology practice. To achieve this, eight semi-structured online interviews were conducted with six radiographers and two radiologists. The Participants were purposively sampled from three different governmental hospitals in Najran, KSA. Audio recordings of the interviews were manually transcribed and analysed by employing thematic analysis. Three themes emerged from the interviews: (1) the knowledge of radiology professionals about AI, (2) the attitudes of radiology professionals towards AI, and (3) the current AI practice in radiology. Two additional themes focused on the drivers and barriers to AI adoption in Saudi radiology practice were identified. Results The findings revealed that most radiology professionals were adequately knowledgeable about AI and its applications in radiology, although they had received no formal education or dedicated training on AI. Positivity and excitement regarding AI integration were expressed by most of the participants, and all of them were willing to use AI-based tools during their routine work. Furthermore, they generally believed in the positive impact that AI would have on radiology practice and patient care. In current radiology practice, several AI applications were used by some participants. This generally positive attitude was mainly driven by AI-appropriate awareness, Saudi Vision 2030, the perceived benefits of AI, and local champion. Despite the overall positivity, some concerns related to job insecurity, skills degradation, AI’s limited accuracy, and related medico-legal issues were raised by some participants. These concerns, in addition to the lack of AI education and training, AI-related costs, and resistance to change, were considered the main barriers to AI adoption in Saudi radiology practice. This warrants an urgent need to introduce AI-related subjects into Saudi radiology curricula, provide dedicated AI training for radiology professionals, and establish an adoption strategy and clear regulations for AI clinical use.113enArtificial intelligence (AI)Machine learning (ML)Deep learning (DL)RadiographersRadiologistsRadiologyCT practiceexperiencesperceptionsattitudeThesis