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Perceptions of Artificial Intelligence in Accounting Education in Higher Education: A Systematic Literature Review

Author

Listed:
  • Zhou Jingbo

    (Faculty of Education, Universiti Kebangsaan)

  • Mohammad Hafiz Bin Zaini

    (Faculty of Education, Universiti Kebangsaan)

Abstract

The rapid development of artificial intelligence (AI) has significantly reshaped instructional practices in accounting education within higher education institutions. This study conducts a systematic literature review to synthesize current empirical research and address a notable gap in the integrated understanding of instructional practices and perceived outcomes. Guided by the PRISMA 2020 framework, the primary objectives are to identify major research themes and examine how AI is applied, including the associated learning outcomes, benefits, and challenges reported in the literature. The methodology involved a systematic search of three electronic databases, Scopus, Web of Science, and ERIC, retrieving peer-reviewed empirical studies published between 2021 and 2025. A total of 22 articles met the inclusion criteria and were analyzed using a thematic synthesis approach. Results indicate that research is predominantly concentrated on "challenges, risks, and ethical concerns" (59.09%), "adoption and acceptance of AI" (54.55%), and "perceived benefits" (45.45%). Geographically, research is heavily focused on Asian emerging economies, particularly Indonesia and Malaysia, while methodologically, quantitative surveys utilizing structural equation modelling (SEM) prevail over qualitative or experimental designs. Key findings suggest that while AI enhances learning efficiency and higher order skills such as critical thinking, adoption is primarily driven by perceived usefulness and users’ digital competencies. Conversely, barriers such as academic integrity, overreliance, and data privacy remain significant concerns shaping implementation. This review concludes that the current research landscape is primarily technology-adoption oriented, with limited emphasis on pedagogical transformation or learning theory. Future research should move beyond feasibility studies to develop systematic pedagogical frameworks and evaluate the long-term impact of AI on accounting competencies and professional readiness.

Suggested Citation

  • Zhou Jingbo & Mohammad Hafiz Bin Zaini, 2026. "Perceptions of Artificial Intelligence in Accounting Education in Higher Education: A Systematic Literature Review," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 10(3), pages 3184-3198, March.
    • Handle: RePEc:bcp:journl:v:10:y:2026:i:3:p:3184-3198
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    References listed on IDEAS

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    1. Hung Quang Bui & Quyen Thi Bao Phan & Ha Thanh Nguyen, 2025. "AI adoption: a new perspective from accounting students in Vietnam," Journal of Asian Business and Economic Studies, Emerald Group Publishing Limited, vol. 32(1), pages 40-51, January.
    2. Haugland Sundkvist, Charlotte & Kulset, Ellen M., 2024. "Teaching accounting in the era of ChatGPT – The student perspective," Journal of Accounting Education, Elsevier, vol. 69(C).
    3. Hassan Damerji & Anwar Salimi, 2021. "Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting," Accounting Education, Taylor & Francis Journals, vol. 30(2), pages 107-130, March.
    4. Zhou, Aner & Luo, Yan, 2025. "Exploring the impact of generative AI on student learning in accounting," Journal of Accounting Education, Elsevier, vol. 72(C).
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