Author(s)

XiaoFeng Zhang, ZiYang Liu^*

Affiliation(s)

School of Business Administration, Jiangxi University of Fiance and Economics, Nanchang 330000, Jiangxi, China.

Corresponding Author

ZiYang Liu

ABSTRACT

With the popularization of artificial intelligence and the Internet, the operation mode of enterprises in the market economy has also changed, and more stringent requirements are put forward for the recruitment of talents. However, under the traditional business education model, there are still problems such as lack of correlation between theory and practice, lack of comprehensiveness in personnel training, and inability to cross and compound among disciplines, resulting in weak innovation and low interest in business among students with backward teaching methods. Artificial intelligence technology has ushered in new opportunities and challenges for traditional education. A large number of basic management work has been replaced by intelligent and information-based programs. Empowering the education field with artificial intelligence is the essence of the educational reform of The Times. Traditional business students need to learn knowledge other than business to guide practice. In order to meet the market demand, colleges and universities urgently need to use new technologies to reform business education and cultivate composite business talents who are proficient in Internet, artificial intelligence, computer and other technologies for the economy and society. In response to these problems, this paper discusses the impact of artificial intelligence on the reform of business education in the new era and new technology from the aspects of school-enterprise cooperation, teacher-student interaction, interaction between business and other majors, and practical-theory association.

KEYWORDS

Artificial intelligence; Business education; Reformation

CITE THIS PAPER

XiaoFeng Zhang, ZiYang Liu. The reformational impact of artificial intelligence on business education. Journal of Trends in Arts and Humanities. 2024, 1(1): 32-40. DOI: https://doi.org/10.61784/jtah3026. 

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