Policy, Practice, and Future Research on AI in Accounting Education

This concluding chapter synthesizes the transformative impact of artificial intelligence (AI) on accounting education, examining its integration across macro (global trends), meso (institutional strategies), and micro (individual learning experiences) levels. It highlights GAI’s capacity to enable personalized learning, enhance engagement, align curricula with industry demands, and foster sustainable educational practices, while addressing ethical, regulatory, and pedagogical challenges essential for responsible adoption and long-term professional preparation. The chapter employs a comprehensive synthesis of the book’s empirical, theoretical, and case-based contributions, drawing on diverse methodologies including quantitative surveys, qualitative insights, cross-cultural analyses, and institutional case studies. It integrates established frameworks—such as the Technology Acceptance Model, Self-Determination Theory, and Constructivist Learning Theory—to evaluate AI’s pedagogical effectiveness, ethical implications, and alignment with professional competencies. Thematic analysis organizes findings into key domains: theoretical foundations, pedagogical transformation, ethical/regulatory considerations, employability alignment, professional development, and global/cultural perspectives. AI significantly enhances learning efficiency, personalization, and engagement through adaptive content, real-time feedback, and immersive simulations, with evidence of improved comprehension, skill acquisition, and industry readiness. However, challenges persist, including data privacy concerns (prioritized by 80% of surveyed professors), academic integrity risks, algorithmic bias, equitable access disparities, and potential overreliance that may diminish critical thinking. Faculty exhibit greater caution than students, emphasizing the need for structured guidelines, ethical frameworks, and blended human-AI models. Global variations in adoption reflect differences in infrastructure, culture, and regulation, underscoring the importance of culturally responsive implementation to ensure inclusivity and sustainability. This chapter advances the discourse on AI in accounting education by proposing a macro-meso-micro framework that unifies diverse empirical and theoretical contributions, offering a holistic lens for understanding systemic transformation. It refines TAM and SDT through integration of ethical and cultural dimensions, addresses literature gaps in discipline-specific applications, and provides actionable recommendations—including phased integration models, digital literacy training, ethical policy development, and hybrid assessment strategies—for educators, institutions, policymakers, and technology developers. By balancing GAI’s efficiency gains with safeguards for integrity, equity, and human-centered learning, the work establishes a foundation for sustainable, responsible innovation in professional education amid rapid technological change. © 2027 selection and editorial matter, Md Jahidur Rahman, Tarek Rana and Hongtao Zhu; individual chapters, the contributors.