THE CHALLENGES AND LIMITATIONS OF ARTIFICIAL INTELLIGENCE IN EDUCATION: A CRITICAL REVIEW
Keywords:
Artificial Intelligence in Education (AIEd), ethical challenges, algorithmic bias, digital divide, pedagogical implications, data privacyAbstract
Artificial Intelligence (AI) has rapidly transformed the educational sector by enabling personalized learning, intelligent tutoring systems, automated assessment, and administrative support. Despite these benefits, the integration of AI in education is accompanied by several challenges and limitations. This paper critically examines the ethical, technological, pedagogical, and socio-cultural challenges associated with the adoption of artificial intelligence in education. The study is based on a review of existing literature on AI applications in educational environments. The findings reveal that major ethical concerns include data privacy, algorithmic bias, lack of transparency, and the risk of depersonalization in learning. Technological limitations such as inadequate infrastructure, high implementation costs, and lack of technical expertise also hinder AI adoption, particularly in developing countries. Pedagogically, AI systems cannot fully replace teachers due to the importance of human interaction, emotional support, and critical thinking development. Social and cultural constraints such as the digital divide, resistance to technology adoption, and inequality in access to digital resources further limit the effective implementation of AI in education. The paper concludes that while artificial intelligence has significant potential to improve education, its successful implementation requires ethical guidelines, teacher training, infrastructure development, and inclusive policies to ensure equitable access to AI technologies in education.References
Akgun, M., & Greenhow, C. (2021). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. Ethics and Information Technology, 23(3), 431–440. https://doi.org/10.1007/s10676-021-09598-w
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
Ekeh, C., Osei, B., & Mensah, K. (2025). The digital divide and AI adoption in developing nations: A focus on Sub-Saharan Africa. Journal of Global Education Technology, 9(1), 112–130.
Farooqi, A., Khan, S., & Ahmed, M. (2024). The impact of artificial intelligence on modern educational frameworks: A comprehensive review. International Journal of Educational Technology, 15(2), 45–62.
Huang, Y., Saleh, S., & Liu, Z. (2024). Automated assessment systems and artificial intelligence in education: Reliability and validity issues. Computers & Education, 191, 104642.
Karroum, M., & Elshaiekh, N. (2023). Teachers’ readiness for artificial intelligence integration in education. Education and Information Technologies, 28(5), 6123–6140.
Kooli, C. (2023). Chatbots in education and research: A critical examination of ethical implications and solutions. Sustainability, 15(7), 5614. https://doi.org/10.3390/su15075614
Malik, M. (2024). Data governance and policy frameworks for AI in higher education. Journal of Computing Research and Innovation, 9(1), 15–32.
Niveditha, R., Sharma, K., & Patel, R. (2023). Evaluating artificial intelligence systems in education: Performance and fairness considerations. Journal of Artificial Intelligence in Education, 33(2), 210–228.
Rizvi, S. (2023). Infrastructural constraints and social inequalities in the age of AI. Global Journal of Social Sciences, 22(4), 88–104.
Rose, M. (2024). Technological capacity and institutional readiness for AI: A global perspective. Technology in Society, 76, 102456.
Saputra, R., Hidayat, T., & Prasetyo, A. (2023). Curriculum adaptation for artificial intelligence integration in education systems. International Journal of Instruction, 16(2), 321–336.
Semwaiko, L., Mtebe, J., & Raphael, C. (2024). Implementation challenges of artificial intelligence in African education systems. African Educational Research Journal, 12(1), 55–70.
Tahiru, F. (2020). AI in education: Ethical and technical challenges in the era of digital transformation. International Journal of Computer Science and Information Technology, 12(4), 1–15.
UNESCO. (2023). Artificial intelligence and education: Guidance for policy makers. UNESCO Publishing.
Vorobyeva, I., Petrova, N., & Sidorov, A. (2025). Artificial intelligence and curriculum transformation in higher education. Education Sciences, 15(1), 44.
Walter, Y. (2024). Embracing artificial intelligence in education: Teacher training and professional development. Education and Information Technologies, 29(2), 1421–1438.
World Bank. (2023). Broadband connectivity and educational equity in developing regions. World Bank Group.
Zhai, X., Chu, H. E., Chai, C. S., Jong, M. S. Y., Iivari, N., & Spector, J. M. (2021). A review of artificial intelligence in education: The state of the art and future directions. Computers and Education: Artificial Intelligence, 2, 100034. https://doi.org/10.1016/j.caeai.2021.100034
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2026 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, adaptation, and reproduction in any medium, provided that the original work is properly cited.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors are permitted to post their work online in institutional/disciplinary repositories or on their own websites. Pre-print versions posted online should include a citation and link to the final published version in Journal of Librarianship and Scholarly Communication as soon as the issue is available; post-print versions (including the final publisher's PDF) should include a citation and link to the journal's website.
