Research on the Innovative Mode and Optimization Path of Deep Integration of Artificial Intelligence Technology and Graduate Education Management Service in Finance and Economics Universities

Shunjia Che, Ying Wang

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¹ National Academy of Financial and Economic Strategy, Central University of Finance and Economics, Beijing 100081, China,

² Office of Development Planning (Discipline Construction Office), Central University of Finance and Economics, Beijing 100081, China,

erd 2026 , 8(2), 234–240; https://doi.org/10.26689/erd.v8i2.14327

© 2026 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )

Abstract

As the new wave of technological revolution and industrial transformation progresses, artificial intelligence is reconfiguring higher education paradigms, rendering the modernization of graduate education management services a crucial contemporary challenge. This study centers on finance and economics universities, delving into the inherent logic, challenges, and development prospects of integrating AI into graduate education management services. Research reveals that these institutions currently encounter challenges such as data silos and inflexible processes, for which AI presents potential solutions. The paper formulates a “trinity” integrated innovation model consisting of four core modules, propelling the shift of graduate education management services from being experience - based to data - driven, from standardized to personalized, and from passive response to proactive service. Moreover, systematic optimization approaches are put forward to offer theoretical and practical guidance for the intelligent transformation of finance and economics universities, promoting reforms in the cultivation of high - level financial professionals.

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