Artificial Intelligence Adoption Intensity and Employee Job Well-being: Analysis and Countermeasures Based on Knowledge-Based Work

DOI

10.2991/978-94-6239-701-9_54How to use a DOI?

Keywords

Artificial Intelligence Adoption Intensity; Job Happiness; Knowledge Work; Employee Well-being

Abstract

As artificial intelligence technology continues to be embedded in organizational contexts, its impact on employee work experience and subjective well-being has gradually become an important topic of academic concern. Compared to existing research that largely explores the impact of AI on work from the perspectives of technological substitution and risk, this paper, based on the real-world context of knowledge-based work, focuses on the mechanisms by which the intensity of AI adoption may positively influence employee job well-being. To address this issue, this paper systematically analyzes the intrinsic relationship between the intensity of AI adoption and employee job well-being from three aspects: workload, emotional experience, and work flexibility. Furthermore, AI significantly enhances employee work flexibility and autonomy in supporting flexible work arrangements, intelligent task allocation, and personalized work support, creating favorable conditions for work-life balance. Building upon this foundation, this paper further proposes three countermeasures from a management practice perspective: optimizing AI application scenarios to continuously reduce low-value burdens, incorporating efficiency goals and employee experience goals into a unified evaluation framework, and enhancing work flexibility and autonomy through AI tools. The findings of this paper expand the theoretical perspective on AI and job well-being research, providing a new explanatory path for understanding the positive humanistic effects of AI in organizations, and offering valuable insights for enterprises to achieve synergistic development of efficiency improvement and employee well-being in the process of promoting AI applications.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shifeng Chen
PY  - 2026
DA  - 2026/07/30
TI  - Artificial Intelligence Adoption Intensity and Employee Job Well-being: Analysis and Countermeasures Based on Knowledge-Based Work
BT  - Proceedings of the 2026 11th International Conference on Social Sciences and Economic Development (ICSSED 2026)
PB  - Atlantis Press
SP  - 528
EP  - 536
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-701-9_54
DO  - 10.2991/978-94-6239-701-9_54
ID  - Chen2026
ER  -