Artificial intelligence (AI) is increasingly used to support various aspects of healthcare. However, the implementation of AI in primary healthcare (PHC) requires a better understanding of its impact on fundamental aspects of quality. This systematic review aims to investigate the role of AI in improving the most important dimensions of quality in primary healthcare, in particular, access, continuity, efficiency, communication, and coordination. Three databases were used for the search, namely PubMED, Scopus, and WoS. The analysis includes articles published between 1 January 2020 and 31 March 2025 in peer-reviewed journals. The search strategy includes a combination of keywords related to AI and specific dimensions of primary healthcare quality. After considering all eligibility criteria based on the PICo framework, 34 studies were included in the analysis. Firstly, the study shows that the use of AI in primary healthcare primarily affects the efficiency of care by supporting the diagnosis of various health problems. Secondly, AI can enhance healthcare accessibility by improving access to specialist services and adapting this care to the needs of patients. In the administrative area, it can optimize access by managing service queues. There is also a growing body of evidence of supporting AI’s role in family doctor-patient communication. However, no evidence currently exists of a beneficial effect of AI on improving coordination and continuity in primary care.