<![CDATA[Breast cancer currently positioned as the leading cause of cancer-related mortality among women in Indonesia, highlighting the urgent need for early detection and accurate diagnosis. AI-assisted mammography is one of a potential solution to detect the cancer early and reduce radiologist workload. However, the adoption of AI mammography remains limited, due to skepticism among healthcare professionals, and a lack of patient awareness. This study aims to evaluate the acceptance of AI mammography using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, by incorporating insights from both healthcare professionals and female patients aged 30 and above. A mixed-method approach was employed, quantitative surveys from 480 women and interviews 8 healthcare professionals. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions significantly impact Behavioral Intention to adopt AI mammography. However, the relationship between Behavioral Intention and actual Use Behavior did not meet reliability and validity thresholds, suggesting that adoption is still in its early phase. Key barriers identified include limited AI exposure, infrastructure disparities, regulatory constraints, and concerns over job displacement among radiologists.]]>
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