Reforming Auditing Education in the AI Era: A Three-Stage Progressive Teaching Model and Its Policy Implications for Higher Education

Abstract

As artificial intelligence and digital technologies become deeply embedded in the auditing profession, the structural gap between conventional university curricula and evolving industry demands has grown increasingly pronounced. This paper reports on a systematic teaching reform of an undergraduate Auditing course, validated across multiple academic cycles, which addresses three core pedagogical pain points: fragmented knowledge structures, the failure to integrate AI and digital tools into instruction, and insufficient team-based project experience. Drawing on diagnostic surveys of 225 students, the course was redesigned around a "Three-Stage Progressive" model encompassing two coordinated innovations: a "Three-Module, Five-Dimensional Integration" content restructuring, and a dual-track approach combining AI-driven instructional methods with team-based project learning and portfolio assessment. Post-reform data show significant improvements in student academic performance, digital competency, and professional identity. On this basis, the paper advances five higher education policy recommendations for reforming accounting and auditing programmes in the AI era, addressing curriculum governance, industry-embedded practicum frameworks, and competency-oriented assessment systems.