Definitions for artificial intelligence (AI) have evolved over time and continue to adapt as technology and research advances. Domingos [10] viewed artificial intelligence as machine learning, which aimed to create an algorithm that could learn from the data provided. Tegmark [11] suggested that AI was an entity of non-biological means that could evolve and adapt to different types of situations, which could, in turn, have a significant impact on society. In the same line, Lee [12] described AI not just as a technology, but also as a force that was redefining economic dynamics globally. He added that AI acted as a technological superpower that could change power structures, with China and Silicon Valley, in the United State, as major players in this revolution. He argued that, in the coming decades, AI would influence economic dynamics, the behavior of societies, and international relations. From another perspective, Marcus and Davis [13] argue that, although impressive progress had been made in AI development, AI had limitations of its own, especially in tasks that required reasoning and an understanding of context. They advocated a vision of AI that not only relied on deep learning, but also added symbolic reasoning, logic, and knowledge of the real world. They added that true artificial intelligence needed a combination of approaches and techniques. Furthermore, Crawford [14] stressed that AI was much more than a technology, highlighting its physical and political impact. He criticized viewing AI as an “intangible”, stressing the importance of taking into account its ethical, socioeconomic, and environmental consequences.

AI has been integrated into almost every part of society. Its ability to process and learn from vast volumes of data has changed the way numerous organizations operate. Moreover, with the emergence of end-user applications, AI is now an everyday tool for workers, professionals and other members of today’s society [15]. An example of this was observed in healthcare, where artificial intelligence, through the use of machine-learning algorithms, has spurred the advancement of clinical research. This has enabled the early detection of disorders such as diabetes and cancer, optimizing the exchange of medical data and benefiting patients [16]. In transportation, the presence of AI manifested with autonomous vehicles and systems that improved routes and optimized fuel consumption, advancements with the potential to improve traffic problems [17]. In retail, personalized recommendations, automated inventory management, and trend analysis have improved the customer experience and optimized business processes [18]. In the financial sector, AI has improved fraud detection and risk management, and with the presence of robotic financial advisors, banking services have been transformed, improving the positioning of these institutions through their users [19]. Another important sector where AI has the potential to have a transformative impact is in education. In this sense, ref. [20] maintained that in Latin America, AI has influenced higher-education institutions, transforming learning and teaching processes. This impact has been decisive for the future of higher education, especially considering that AI has the potential to personalize learning by creating online content while considering the needs and expectations of students. In this regard, the authors [6] added that AI tools offered specific and contextual solutions to optimize the solution of academic problems. In addition, AI trends were driving globalized teaching–learning models, which undoubtedly promoted the socialization of knowledge. However, the authors added that AI, despite its potential, was unlikely to completely replace traditional teaching.

Several authors have argued that education, as an agent of the socialization of knowledge, should take advantage of the benefits of AI in the training context [8] in order to maximize educational achievements. To achieve this purpose, multiple technologies could be applied in the classroom, including virtual reality, augmented reality, AI chats, and video games, among others [18,21]. These enriching applications promoted the creation of more dynamic and disruptive classrooms, such as the design of virtual environments for instant student exploration [22,23]. After observing the points of view of various authors on the relationship between AI and education, it was clear that this technology could revolutionize current methods in this sector. The benefits, the challenges, and the applications of AI in education can be observed clearly in Figure 1. This diagram summarizes the main areas of interaction between AI and higher education, providing a broad view of the topic under analysis.

This diagram shows some of the dimensions in which AI could impact higher education. From the personalization of learning to the development of advanced virtual classrooms, to a more interactive student experience through the development of AI-based end-applications, this technological advancement could transform education through a more adaptive, interactive, and globalized environment. However, it would be necessary to take into account the ethical challenges and uses when integrating this technology into the educational environment.

As AI continues to advance and adapt to the dynamic needs of society, there is a need for the academic community to understand its potential and limitations. Integrating AI into education could also open new avenues for research, collaboration, and innovation. However, as with any emerging technology, it would be essential to address ethical concerns, ensure equity of access, and ensure that the adoption of AI in education reinforces, rather than minimizes, the core values of education.