Amid the wave of digital transformation, generative AI is profoundly reshaping work patterns across industries. This study focuses on the dual impact of generative AI-driven job reshaping on the sustainability of employee creativity. The paper first elucidates the essence of generative AI and job reshaping, analyzing how generative AI alters work content, relationships, and cognition through functional restructuring, communication restructuring, and value restructuring. The core research lies in dialectically examining its mechanisms: On one hand, generative AI catalyzes creative generation, optimizes cognitive resources, empowers higher-order thinking, and expands creative networks—providing new momentum for sustained creativity. On the other hand, it may lead to the atrophy of foundational creative skills, exacerbate risks of homogenization in innovation ecosystems, and erode intrinsic motivation for creation, posing potential threats to creativity's long-term sustainability. This study aims to uncover this double-edged sword effect, ultimately proposing systematic recommendations at the organizational level. These recommendations seek to steer the work transformation driven by generative AI toward a future that enhances rather than suppresses human creativity, providing theoretical references and practical guidance for organizations to build sustainable innovation ecosystems.

Xiaogang Ren. The Impact of Generative AI-Driven Job Reshaping on Creativity Sustainability. The Frontiers of Society, Science and Technology (2025), Vol. 7, Issue 7: 15-21. https://doi.org/10.25236/FSST.2025.070703.

[1] Huang Jun, Lin Fei, Yang Jing, et al. Prompt Engineering for Large Generative AI Models: Methods, Current Status, and Future Prospects. Journal of Intelligent Science and Technology, 2024, 6(02): 115-133.

[2] Liu Hongwei, Ma Youru. Generative Artificial Intelligence and Green Productivity Cultivation: Key Elements, Driving Pathways, and Policy Recommendations. Academic Circle, 2025(03):78-88. 

[3] Wang Zhen. Formation and Influence Mechanisms of Teamwork Reshaping. Psychological Science, 2020, 28(03): 390-404

[4] Wen Qing. Empowerment and Reshaping. Research on Open Education, 2025, 31(03): 2.

[5] Li Xiaoyan. Job Redesign: Non-Traditional Approaches to Work Design. Modern Enterprise, 2019, (01): 46-47.

[6] Lin Li, Zhu Jingjing. Antecedents of Generative AI Usage and Its Impact on Job Performance: A Digital Work Reshaping Perspective. China Human Resources Development, 2025, 42(02): 57-78.

[7] Shahzad M F, Xu S, Zahid H.Exploring the impact of generative AI-based technologies on learning performance through self-efficacy, fairness & ethics, creativity, and trust in higher education. Education and Information Technologies, 2025, 30(3):3691-3716.

[8] Fu B, Hadid A, Damer N. Generative AI in the context of assistive technologies: Trends, limitations and future directions. Image and Vision Computing, 2025, 154: 105347.

[9] Hilario E , Azam S , Sundaram J ,et al.Generative AI for pentesting: the good, the bad, the ugly.International Journal of Information Security, 2024, 23(3).

[10] Zhou T, Zhang C. Examining generative AI user addiction from a CAC perspective. Technology in Society, 2024, 78: 102653.

[11] Wang P Q.Personalizing guest experience with generative AI in the hotel industry: there's more to it than meets a Kiwi's eye. Current Issues in Tourism, 2025, 28(4):527-544.

[12] Al-Emran M, Abu-Hijleh B, Alsewari A R A. Examining the impact of Generative AI on social sustainability by integrating the information system success model and technology-environmental, economic, and social sustainability theory. Education and Information Technologies, 2025, 30(7): 9405-9426.

[13] Tian Xianpeng, Xiao Zhiqi. Academic Ethics and Risk Prevention in Graduate Research Writing Empowered by Generative AI. Modern Educational Technology, 2024, 34(08): 23-32.

[14] Garcia M B. The paradox of artificial creativity: Challenges and opportunities of generative AI artistry. Creativity Research Journal, 2024: 1-14.