Digestive cancer is one of the leading causes of mortality worldwide, with an increasing incidence in several regions, including Latin America. Early detection of these pathologies is crucial to improve clinical outcomes and reduce the economic burden associated with the treatment of advanced stage cancers. This review is justified by the need to address the significant challenge of early detection of digestive cancer, especially in asymptomatic patients. The main objective of this study is to learn about the benefits of artificial intelligence (AI) in improving early diagnosis of digestive cancers, evaluating its effectiveness in identifying early lesions and its impact on diagnostic accuracy. Through a systematic review of the literature, and the application of the PRISMA model for its development, we examine various applications of AI as applied to medicine and specifically to the diagnosis of digestive cancers, including computer-aided detection (CADe), and discuss the benefits of its implementation in clinical practice. The findings suggest that AI has the potential to transform digestive cancer diagnosis, although further research is required to overcome current barriers and validate its use in clinical settings
