Deskilling refers to the gradual weakening of clinical judgment, procedural competence, or diagnostic reasoning due to over-reliance on automated systems.[1] In health education, it manifests itself in the erosion of core competencies, as tasks are delegated to machines instead of being performed by skill.[1] Automation bias arises from pressure for efficiency, cognitive overload, or the mistaken belief that a machine knows better.[1] The highest risk of deskilling occurs with passive use of AI, such as uncritical acceptance of outputs, shortcut learning, or insufficiently specified inputs.[4] For mitigation, a human-in-the-loop approach is recommended, where physicians remain the final decision makers and document their rationale.[1] Education should emphasize re-skilling, mentorship and activities that algorithms cannot imitate.[1] AI is neither a savior nor a saboteur, but a tool that changes the roles of humans if only used to supervise machines.[1]