Generative AI in Accounting Education: Empirical Evidence on Personalized Learning and Ethical Challenges

This study examines the integration of generative artificial intelligence (AI) in accounting education, focusing on its capacity to support personalized learning and the associated ethical implications for students and professional development. A mixed-methods design was employed, combining an online questionnaire distributed to accounting students at a Chinese-foreign joint university with a systematic literature review. The survey captured usage patterns, preferred AI-assisted tasks, perceived benefits, and ethical concerns. Findings were interpreted through established educational frameworks, including Vygotsky’s Zone of Proximal Development and Gardner’s Theory of Multiple Intelligences. Accounting students widely adopt generative AI for personalized learning, utilizing it for real-time concept explanation, technical content translation, summarization of complex materials, customized practice generation, study planning, and stress relief through conversation. However, participants express significant concerns about data privacy, algorithmic bias, risks to academic integrity, and potential erosion of critical thinking and ethical reasoning skills, which are vital to the accounting profession. This research provides novel empirical insights into generative AI’s application in the specialized context of accounting education, bridging educational theory with discipline-specific needs. It highlights opportunities for enhanced accessibility and efficiency while emphasizing ethical safeguards essential to preserving professional judgment and integrity. © 2027 selection and editorial matter, Md Jahidur Rahman, Tarek Rana and Hongtao Zhu; individual chapters, the contributors.