Exploring AI Financial Practical Teaching Pathways for Higher Vocational Accounting Majors in the Digital Intelligence Era

Zhou Bin, Zhang Dingfu, Wan Ziqi

Chengdu Vocational University of the Arts

Abstract：

The deep integration of the digital economy and artificial intelligence is reshaping corporate finance, shifting it from a traditional accounting-oriented function to an intelligent analysis and value-creation model. Robotic process automation (RPA), intelligent tax review, and big-data financial analytics have fundamentally altered the competency requirements for accounting roles. As the primary channel for cultivating frontline technical financial talents, higher vocational colleges face persistent challenges in their practical teaching: outdated curricula, narrow training scenarios, low digital-intelligence integration, and rigid evaluation mechanisms. These issues result in a serious mismatch between talent cultivation and industry digital-intelligence demands. Based on vocational education orientation and industry transformation trends, this paper systematically analyzes the practical dilemmas of AI financial training in higher vocational colleges. It proposes optimized pathways from five dimensions: curriculum reconstruction, training platform development, teaching mode innovation, faculty capacity building, and evaluation system improvement. The goal is to enhance students' digital intelligence practical abilities and job adaptability, thereby offering practical references for teaching reform and the high-quality development of higher vocational accounting programs.

Key Words：

digital intelligence; higher vocational finance and accounting; AI finance; practical teaching; teaching reform