Integration of Artificial Intelligence in Higher Education in America: A systematic literature review

Pachas Sánchez L.K.; Olivo Leandro R.E.; Junco Gutiérrez M.C.; Fernández-Flores S.M. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2026) · DOI: 10.18687/laccei2026.1.1.862

Resumen

Artificial intelligence (AI) has become an essential component of higher education, especially due to the advancement of generative AI, which has transformed pedagogical practices and teaching-learning methods. The objective of this systematic literature review (SLR) is to analyze the impact of AI on students and teachers compared to those who continue to use traditional learning methods. To this end, the PRISMA 2020 protocol and the PICO method were applied through an exhaustive search of the Scopus database, yielding a total of 33 documents that met the established inclusion and exclusion criteria. The results show a sustained increase in publications by 2025 and a multidisciplinary character, with contributions from the social sciences, computer science, and engineering. Among the benefits highlighted are personalized learning, improved feedback, support for teaching, and increased student motivation. However, limitations also emerge, such as technological dependence, insufficient teacher training, institutional resistance, a decline in critical thinking, and the absence of robust ethical frameworks. Overall, the RSL indicates that AI has a mostly positive effect on higher education, facilitating time management, comprehension of complex content, and enabling more adaptive learning experiences. Nevertheless, challenges persist related to the reliability of AI-generated information, the lack of institutional regulations, and technological gaps stemming from internet access or the cost of advanced tools.

Instituciones: Universidad Tecnológica del Perú; Universidad Nacional Federico Villarreal