Artificial intelligence, especially generative AI, has experienced exponential growth since 2020, profoundly transforming the educational landscape. The launch of ChatGPT on November 30, 2022, marked a milestone, reaching 5 million users in just five days and surpassing 100 million by January 2023, according to data presented at Deep Seek forums. In higher education, generative AI is revolutionizing teaching, research, and management. However, it faces crucial challenges: the need for appropriate regulation and its democratization to ensure universal access. In teaching, AI offers applications such as adaptive learning, which personalizes the educational process according to each student's abilities; augmented pedagogy, which integrates traditional methods with advanced technology; and intelligent tutoring, which provides continuous personalized support. Large language models (LLMs), such as ChatGPT, Microsoft’s Copilot, or Google DeepMind’s Gemini, enable the generation and understanding of natural language, facilitating complex tasks and enhancing the educational experience. Other advantages include chatbots capable of detecting and assisting students in emotional vulnerability, as well as transcription tools that benefit international students. For educators, AI automates administrative tasks, aids in material preparation and assessment, freeing up time for research and direct interaction with students. However, as Leire Nuere points out, the role of the teacher remains irreplaceable due to their ability to inspire and guide. In research, AI allows for the analysis of large volumes of data, the creation of models and simulations, the automation of processes, and the promotion of interdisciplinary collaboration. Its applications have already led to advancements in medicine, meteorology, astronomy, and genetics, among other fields. Despite its benefits, the integration of AI in higher education faces significant challenges. Continuous training for faculty is essential, as students sometimes surpass their teachers in using these tools. Additionally, funding represents an obstacle, requiring partnerships between universities and companies to finance technological implementation and updates. Regulation and ethical use of AI are priorities. The European Union has promoted the first AI law, based on risk classification, and organizations like UNESCO have established ethical frameworks for its responsible use. It is also essential to combat algorithmic biases, as AI can reproduce and amplify prejudices present in training data. The environmental impact of AI, due to its high energy consumption, and the need to make it accessible to everyone, regardless of their technological experience, are other challenges to consider. Initiatives like AI Alliance aim to promote inclusive and safe AI. Finally, experts like Pedro Mercado, rector of the University of Granada, warn about the stress that the rapid adoption of AI can generate in university communities, emphasizing the importance of accompanying this process with psychological support and training. AI is here to stay, and its potential in higher education is undeniable. However, its adoption requires overcoming barriers in training, funding, regulation, ethics, equity, and sustainability. Source: lne.es