Artificial Intelligence (AI) has been incorporated into teaching-learning processes with great expectations in recent years. University chemistry education is no exception, where Machine Learning and Natural Language Processing stand out. Due to the dizzying advances in this field, it is necessary to verify the state of the art of implementing this powerful tool in teaching chemistry at the university level and its strengths, weaknesses, and incorporation as part of university curricula. A systematic search of publications from the last five years (between 2019 and 2024) was carried out in recognized databases. Using these data, a qualitative/comparative analysis of the approaches and contributions of the selected literature was carried out. The AI revolution has reached university chemistry education. However, it is still incipient, with significant advantages and benefits, and in contrast, some negative considerations from the ethical and reliability point of view. By balancing these antagonistic positions, AI is projected as a vital tool in teaching-learning processes that will save resources and time, increasing their efficiency and effectiveness. It is recommended that the concerns arising from these tools be addressed to minimize them and gradually incorporate AI into university chemistry through chatbots or more specific applications, depending on the subject addressed.