magazinelogo

The Educational Review, USA

ISSN Online: 2575-7946 ISSN Print: 2575-7938 CODEN: TERUBB
Frequency: monthly Email: edu@hillpublisher.com
Total View: 7148809 Downloads: 1509041 Citations: 1026 (From Dimensions)
OpenAlex-based citation data
  • citations

    1417
  • h-index

    13
  • i10-index

    14
ArticleOpen Access http://dx.doi.org/10.26855/er.2026.05.011

Artificial Intelligence and the Digital Transformation of Higher Education: Opportunities, Challenges and Strategic Paths for High-quality Development

Xin Wang

Xi'an Mingde Institute of Technology, Xi'an 710124, Shaanxi, China.

*Corresponding author: Xin Wang

Published: May 30, 2026

Abstract

The rapid development of artificial intelligence is profoundly reshaping the form and core of higher education, driving its comprehensive transformation towards digitalization and intelligence. This transformation is not just an upgrade of the technological system, but an all-round change of educational concepts, teaching models and governance systems, providing a historic opportunity for the high-quality development of higher education. This article focuses on the current technological trends in the development of artificial intelligence, explores the path of digital transformation in colleges and universities, and presents the problems and specific countermeasures that colleges and universities face in digital transformation in the era of artificial intelligence. It proposes strategic paths such as establishing the transformation concept of “people-oriented, digital intelligence for good”, building an AI literacy improvement system for all staff, promoting the deep integration of AI and curriculum, and building an open, secure and intelligent public digital education base, with the aim of providing theoretical references and practical guidance for the leapfrog development of higher education in China in the intelligent era.

Keyword

Artificial intelligence; high-quality development; digital transformation; higher education

References

An, B. (2026). Research on the performance evaluation of artificial intelligence education policies in colleges and universities. Shandong University of Finance and Economics.

Chen, B. (2026). Challenges and strategies of generative AI empowering personalized vocational education for college students: A case study of applied universities. Beijing Science and Technology News, 003.

Hao, Z., Ma, L., Long, Y., et al. (2026). Research on the motivations, models and evolution mechanisms of teaching innovation by university teachers in the era of artificial intelligence. Chinese Journal of Educational Technology, 7, 97-105.

Li, Z., Zhai, K., Tao, S., et al. (2026). Research on the path of artificial intelligence empowering ideological and political education in colleges and universities to promote employment development of college students from the perspective of new quality productivity. Journal of Qingdao Agricultural University (Social Science Edition), 1-9.

Lu, X., & Zou, T. (2026). Motivations, practices and lessons of AI ethics education in American universities: A case study based on five universities. Natural Dialectics Research, 6, 132-141.

Lu, Y. (2026). Research on the practical path and risk governance of artificial intelligence empowering precise ideological and political education in colleges and universities. Journal of Social Sciences of Jiamusi University, 44, 68-70+75.

Sun, H., & Wu, Y. (2026). Artificial intelligence era of the challenges facing university education model and the optimization countermeasures. Journal of Hebei University of Economy and Trade (Comprehensive Edition), 26(2), 81-86.

Wang, M., Ni, Z., & Zhou, X. (2026). The application of artificial intelligence in ideological and political education in colleges and universities: A case study of integrating “five-color Jilin” into ideological and political education. Decision Making and Information, 7, 83-88.

Copyright

© 2026 by the author(s).
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license, which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not modified or adapted.
https://creativecommons.org/licenses/by-nc-nd/4.0/

How to cite this paper

Artificial Intelligence and the Digital Transformation of Higher Education: Opportunities, Challenges and Strategic Paths for High-quality Development

How to cite this paper: Xin Wang. (2026). Artificial Intelligence and the Digital Transformation of Higher Education: Opportunities, Challenges and Strategic Paths for High-quality DevelopmentThe Educational Review, USA10(5), 325-329.

DOI: http://dx.doi.org/10.26855/er.2026.05.011