Artificial intelligence is gradually but surely having an increasing influence in almost every industry of today’s society. Machine learning, a sub-branch of AI trains computers to learn from specific field datasets by analysing the complex patterns, correlations and relationships within different parameters in the dataset. This chapter aims to discuss the potential ways in which ML could reshape the current diagnosing approach of primary healthcare in Hong Kong. One example of its potential use is aiding early diagnosis of breast cancers. Exploiting current large breast cancer tumour biopsy datasets in Hong Kong enables the production of machine learning models that could distinguish between benign and malignant breast tumours accurately, serving as a supportive diagnosing tool for practitioners. If implemented correctly, machine learning has the potential to dramatically improve breast cancer detection rates, enabling more accurate early detection and improving prognosis for current and future cancer patients. These models also have the potential to reduce overdiagnosis and alleviate the already enormous healthcare burden of the Hong Kong healthcare system, as it reduces resource wasting and unnecessary patient distress. The potential of AI in multiple settings will also be explored in this article. Despite the potential, introducing new technologies in healthcare remains a challenge as various limitations and challenges need to be addressed through multi-sector collaboration. This is still a fairly new and premature concept that needs more recognition to open the doors to more similar local research and experiments.