In modern ophthalmology, the advent of artificial intelligence (AI) is gradually showing promising results. The application of complex algorithms to machine and deep learning has the potential to improve the diagnosis of various corneal and ocular surface diseases, customize the treatment, and enhance patient outcomes. Moreover, the use of AI can ameliorate the efficiency of the health-care system by providing more accurate results, reducing the workload of ophthalmologists, allowing the analysis of a big amount of data, and reducing the time and resources required for manual image acquisition and analysis. In this article, we reviewed the most important and recently published applications of AI in the field of cornea and ocular surface diseases, with a particular focus on keratoconus, infectious keratitis, corneal transplants, and the use of in vivo confocal microscopy.