This research aims to deeply analyze the employment risk faced by undergraduates in Fuyang, China under the background of artificial intelligence and propose practical countermeasures. Through the comprehensive use of survey data collection and multi-subject analysis methods, a comprehensive survey was conducted on the employment status of undergraduates in Fuyang, covering multi-dimensional data such as employment rate, employment flow and salary level. At the same time, it deeply analyzed the employment risk such as job substitution risk, skill mismatch, and psychological and cognitive biases brought about by artificial intelligence. Based on this, countermeasures are proposed from four levels: colleges and universities, the government, enterprises and college students themselves, including colleges and universities adjusting professional settings, optimizing curriculum systems, and strengthening practical teaching; the government introduces support policies and guides industrial development; enterprises deepen school-enterprise cooperation and provide timely feedback on talent needs; college students improve their learning ability, cultivate innovation and cross border integration capabilities. The research aims to provide theoretical and practical references for the employment guidance and education policymaking of college students in Fuyang and help alleviate the employment pressure of college students in the artificial intelligence environment.
References
[1] Kuhar, N., Kumria, P., Rani, S. (2024) Overview of applications of Artificial Intelligence (AI) in diverse fields. Application of Artificial Intelligence in Wastewater Treatment, 41-83.
[2] Wang, T. M., Tao, Y., Liu, H. (2018) Current research and future development trend of intelligent robot: a review. International Journal of Automation and Computing, 15(5), 525-546.
[3] Kumar, P. (2024) Managing service flexibility in healthcare for improved customer experience: a data-driven approach. Journal of Strategic Marketing, 32(7), 891-912.
[4] Kong, X., Mo, Z. (2025) The impact of generative Artificial Intelligence on employment in China’s service sector. Journal of Shaanxi Normal University (Philosophy and Social Sciences Edition), 54(01), 102-114.
[5] Martínez-Arellano, G., Ratchev, S. (2025) Towards frugal industrial AI: a framework for the development of scalable and robust machine learning models in the shop floor. The International Journal of Advanced Manufacturing Technology, 138(1), 169-191.
[6] Pearson, S., Curtis, C. (2025) Erotic AI chatbots offer research opportunities for the behavioral sciences. Archives of Sexual Behavior, 54(3), 855-858.
[7] Rahman, M. M. (2023) AI for ADHD: opportunities and challenges. Journal of Attention Disorders, 27(8), 797-799.
[8] Li, L., Cheng, M., Duan, K., Li, W., Zhao, D. (2025) Can public employment services improve employment opportunities of ruralto-urban migrant workers in China? Applied Economics Letters, 32(4), 476-480.
[9] Li, J., Che, T. T., Yang, Y. S. (2021) Artificial Intelligence and employment: substitution or promotion. Dongbei Univ. Financ. Econ, 1, 30-39.
[10] Song, B. (2023) Current research on the impact of Artificial Intelligence on employment and recommendations for mitigation. Vocational Technology, 22(03), 62-68.
[11] Han, C. (2020) Research on educational strategies for college students’ employment attitudes in the age of Artificial Intelligence. Industrial and Technological Forum, 19(04), 177-178.
Share and Cite
Jiao, C. (2025) The Employment Risk and Coping Strategies for Undergraduates in the Era of Artificial Intelligence: A Qualitative Research in Fuyang, China. Global Education Bulletin, 2(3), 19-26. https://doi.org/10.71052/grb2025/MTFL1385