AI in Higher Education - A Paradigm Shift in Accounting and Business Pedagogy

This introductory chapter provides a comprehensive foundation for understanding the transformative role of artificial intelligence (AI) in accounting education. It examines GAI’s evolution from earlier adaptive systems to advanced large language models, analyzes its pedagogical implications, theoretical underpinnings, ethical challenges, and alignment with professional demands, while establishing the book’s macro-meso-micro framework to guide exploration of global trends, institutional strategies, and individual learning experiences in an AI-driven educational landscape. The chapter synthesizes multidisciplinary perspectives through a structured literature-informed narrative, integrating theoretical frameworks—Technology Acceptance Model (TAM), Self-Determination Theory (SDT), Constructivist Learning Theory, Neutralization Theory, and Ethical Decision-Making Theory—to contextualize AIadoption and impact. It draws on empirical evidence from global surveys, case studies (particularly Sino-foreign universities), and thematic analysis of opportunities (personalization, engagement, employability) and challenges (integrity, privacy, equity). The macro-meso-micro lens organizes discussion across systemic trends, institutional policies, and learner experiences, setting the stage for subsequent chapters’ focused investigations. AIfundamentally reshapes higher education pedagogy by enabling interactive, student-centered experiences that transcend traditional methods, offering personalized feedback, scenario simulation, and efficiency gains in complex accounting tasks. Widespread adoption reflects perceived usefulness and motivational benefits, yet reveals tensions: student enthusiasm for efficiency contrasts with faculty caution regarding academic integrity, data privacy (80% professor concern), bias, overreliance, and equity disparities. Theoretical alignment with TAM (usefulness/ease of use), SDT (autonomy/competence/relatedness), and constructivism (active knowledge construction) support GAI’s potential, while neutralization and ethical decision-making theories highlight rationalization of misuse and moral dilemmas. Institutional policies and industry alignment increasingly emphasize digital literacy and ethical frameworks to balance innovation with professional standards. This chapter establishes a novel macro-meso-micro analytical framework that unifies fragmented research on AI in accounting education, bridging global adoption patterns, institutional governance, and micro-level learner dynamics. It extends TAM and SDT by incorporating ethical, cultural, and regulatory dimensions specific to precision-dependent disciplines, addresses critical literature gaps in discipline-specific applications, and provides a foundational reference for educators, administrators, policymakers, and researchers. By advocating responsible, evidence-based integration that preserves critical thinking, integrity, and human mentorship while preparing graduates for AI-augmented professions, the work lays the essential groundwork for sustainable pedagogical innovation amid rapid technological change. © 2027 selection and editorial matter, Md Jahidur Rahman, Tarek Rana and Hongtao Zhu; individual chapters, the contributors.