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Cited by 16Artificial Intelligence in EducationTechnology Adoption and User BehaviourEducational Innovations and Challenges

Adoption of artificial intelligence in higher education: a diffusion of innovation approach

Gutiérrez-Leefmans, Manuela, Picazo-Vela, Sergio, Kareem, Olanrewaju·2026·The TQM Journal
DOI 10.1108/tqm-12-2024-0523
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Abstract

Purpose Quality education is part of the United Nations’ goals for 2030, and artificial intelligence (AI) poses both an opportunity and a challenge to achieve it. This study aims to understand the landscape and level of innovativeness when adopting AI. We use the diffusion of innovation theory (DOI) to understand the adoption of AI among students in a Latin American university. Design/methodology/approach A sample of 280 university students at a business school was used to test the hypotheses using Structural Equation Modeling (SEM). Findings The study found that the second largest group, after the “late majority”, is “early adopters.” The results also show that there is a positive relationship between relative advantage, observability, trialability, compatibility and AI adoption. The factor of complexity, however, did not result in significant results, indicating that it does not represent an obstacle for students to adopt AI for learning purposes. Research limitations/implications The findings have important implications for higher education institutions and professionals. This is particularly relevant in a context where students easily adopt digital technology. Practical implications Centennials are a generation that changes slightly the DOI curve. With a good number of early adopters, HEIs need to be prepared in terms of infrastructure and training. Professors should be aware of the size of this group, which is no longer one or two exceptional students. Although they may…

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  • Gutiérrez-Leefmans (2025) reporta en un estudio cuantitativo que la adopción de herramientas de aprendizaje adaptativo en instituciones mexicanas y chilenas ha crecido un 20% anual desde 2021, aunque subraya limitaciones como la falta de interoperabilidad de datos entre plataformas y la escasa formación técnica del profesorado.

    “Más recientemente, Gutiérrez-Leefmans (2025) reporta en un estudio cuantitativo que la adopción de estas herramientas en instituciones mexicanas y chilenas ha crecido un 20% anual desde 2021, aunque subraya limitaciones como la falta de interoperabilidad de datos entre plataformas y la escasa formación técnica del profesorado [11].”

    From Avances, Retos Éticos y Perspectivas de la Inteligencia Artificial (IA) en la Educación de América Latina (2025) · cites this paper as [11]

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Authors
Gutiérrez-Leefmans, M., Picazo-Vela, S., & Kareem, O.
Affiliations
Universidad de las Américas Puebla (MX)
ORCID
Venue
The TQM Journal
Publisher
Emerald
Published
2025-06-16
Volume
38
Issue
3
Pages
633-654
ISSN
  • 0954-478X (ISSN-L)
  • 1754-2731
  • 1754-274X
DOI
10.1108/tqm-12-2024-0523
OpenAlex
W4411294646
Cited by
16
References
12
Citations by year
2026: 13 · 2025: 3
FWCI
16.77
Type
journal article
Language
en
Open access
closed
Locations
The TQM Journal (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Physical Sciences › Computer Science › Information Systems › Educational Innovations and Challenges
Keywords
artificial intelligence adoption, higher education, diffusion of innovation theory, university students, early adopters, relative advantage, observability, trialability, compatibility, complexity, generational cohorts, Generation Z, artificial intelligence in education, Latin America

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