The Stimulation of Employee Creativity by Artificial Intelligence Technology in Different Work Environments and Its Impact Mechanisms

Shilong Li

doi:10.47297/taposatWSP2633-456938.20250603

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The Stimulation of Employee Creativity by Artificial Intelligence Technology in Different Work Environments and Its Impact Mechanisms

Volume 6, Issue 3

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The Stimulation of Employee Creativity by Artificial Intelligence Technology in Different Work Environments and Its Impact Mechanisms
The Stimulation of Employee Creativity by Artificial Intelligence Technology in Different Work Environments and Its Impact Mechanisms
Kaplan Higher Education Academy, Sanhe, Langfang, 065201 Hebei, China
Vol. 6, Issue 3, Pages: 205-208(2025)
Published：25 March 2025
DOI：10.47297/taposatWSP2633-456938.20250603
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Li Shilong.The Stimulation of Employee Creativity by Artificial Intelligence Technology in Different Work Environments and Its Impact Mechanisms[J].Theory and Practice of Science and Technology,2025,06(03):205-208.
DOI：

Li Shilong.The Stimulation of Employee Creativity by Artificial Intelligence Technology in Different Work Environments and Its Impact Mechanisms[J].Theory and Practice of Science and Technology,2025,06(03):205-208. DOI： 10.47297/taposatWSP2633-456938.20250603.

摘要

Abstract

This paper focuses on the mechanism of how artificial intelligence (AI) technology affects employee creativity in different work environments. Based on Amabile's creativity component theory

a three-dimensional integrated framework of "domain skill empowerment - thinking process reshaping - motivation regulation effect" is constructed

[

]

. Cross-industry case studies in education

finance

technology

and manufacturing show that AI releases cognitive resources by automating repetitive tasks. Its nonlinear output characteristics can stimulate breakthrough inspirations

potentially leading to algorithmic dependence. Task substitution

while enhancing intrinsic motivation

is accompanied by the risk of technological dependence. This paper reveals the significant moderating effect of industry context on the AI action path. This paper confirms the dynamic adaptation mechanism between AI and the work environment and proposes that enterprises should build an agile iterative technology deployment framework based on the characteristics of industry knowledge

and optimize human-machine collaboration efficiency through digital literacy improvement plans and collaborative culture construction.

关键词

Keywords

references

Amabile, T. M. (2018). Creativity in context: Update to the social psychology of creativity. Routledge.

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & company.

Manyika, J., Chui, M., & Miremadi, M. (2017). A future that works: AI, automation, employment, and productivity. McKinsey Global Institute Research, Tech. Rep, 60, 1-135.

Lund, S., Madgavkar, A., & Manyika, J. (2021). The future of work after COVID-19. McKinsey global institute, 18.

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive science, 12(2), 257-285.

Binns, R., Veale, M., & Van Kleek, M. (2017). Like trainer, like bot? Inheritance of bias in algorithmic content moderation. In Social Informatics: 9th International Conference, SocInfo 2017, Oxford, UK, September 13-15, 2017, Proceedings, Part II 9 (pp. 405-415). Springer International Publishing.

Choudhury, P., Foroughi, C., & Larson, B. (2021). Work‐from‐anywhere: The productivity effects of geographic flexibility. Strategic Management Journal, 42(4), 655-683.

Brynjolfsson, E., Rock, D., & Syverson, C. (2021). The productivity J-curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics, 13(1), 333-372.

Acemoglu, D., & Restrepo, P. (2022). Tasks, automation, and the rise in US wage inequality. Econometrica, 90(5), 1973-2016.

Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard business review, 96(4), 114-123.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education promises and implications for teaching and learning. Center for Curriculum Redesign.

Luckin, R., Cukurova, M., & Kent, C. (2021). AI in education: A critical review of the promises and challenges. British Journal of Educational Technology, 53(1), 1-18.

Zawacki-Richter, O., Marín, V. I., & Bond, M. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 16(1), 1-27.

Tondeur, J., Van Braak, J., & Ertmer, P. A. (2017). Understanding the relationship between teachers' pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational technology research and development, 65, 555-575.

Fuster, A., Plosser, M., & Schnabl, P. (2019). The role of technology in mortgage lending. The Review of Financial Studies, 32(5), 1854-1899.

Philippon, T. (2019). The great reversal: How America gave up on free markets. Harvard University Press.

Begenau, J., Farboodi, M., & Veldkamp, L. (2018). Big data in finance and the growth of large firms. Journal of Monetary Economics, 97, 71-87.

Mestikou, M., Smeti, K., & Hachaïchi, Y. (2023). Artificial intelligence and machine learning in financial services market developments and financial stability implications. Financial Stability Board, 1, 1-6.

Hoffman, D. L., & Novak, T. P. (2018). Consumer and object experience in the internet of things: An assemblage theory approach. Journal of Consumer Research, 44(6), 1178-1204.

Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of economic perspectives, 29(3), 3-30.

Deming, D. J. (2017). The growing importance of social skills in the labor market. The quarterly journal of economics, 132(4), 1593-1640.

Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of political economy, 128(6), 2188-2244.

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