Artificial intelligence and higher education: a review of opportunities, risks, and transformations in learning processes
The aim of this study was to analyze the opportunities, risks, and pedagogical transformations associated with the use of artificial intelligence in higher education learning processes. A theoretical review based on documentary analysis was conducted through the critical examination and comparative synthesis of scientific literature published between 2021 and 2026 in databases such as Scopus, Web of Science, and ERIC. The analysis explored the main dimensions through which artificial intelligence is reshaping university teaching and learning, including personalized learning systems, generative AI tools, algorithmic assessment, and emerging ethical and epistemological challenges. The reviewed literature revealed that artificial intelligence offers significant benefits depending on institutional contexts and the pedagogical approaches guiding its implementation, while also posing risks related to academic dependency, superficial learning, and assessment bias. The opportunities and risks identified represent an interdependent tension that influences the effective integration of artificial intelligence into higher education. The findings suggest that the pedagogical transformation enabled by artificial intelligence depends less on the sophistication of the technologies themselves and more on the institutional capacity to establish curricular guidelines, implement ethical policies, and foster critical digital competencies among both teachers and students.