Artificial intelligence (AI) has rapidly evolved over the last several years, giving us a glimpse into the potential of powerful tools in the diagnosis and treatment of ophthalmic disorders. In this chapter, we will review current and potential clinical applications of AI in corneal diseases including dry eye disease, infectious keratitis, keratoconus, and Fuchs endothelial dystrophy. AI modalities in cornea have primarily leveraged imaging platforms to develop deep learning (DL) algorithms. While in various stages of clinical application, many of these algorithms have demonstrated high sensitivity, specificity, and accuracy. Although these models demonstrate significant promise, reports in the literature lack uniformity in data reporting and have variability in patient demographics and study endpoints. With the burgeoning of AI platforms in the diagnosis, management, and prognosis of corneal disease, standardization will become an important next step in applying these platforms across diverse patient cohorts.