Job Crafting and Incentive Evolution in the AI Era: A Structural Framework for the Rise of Verification Labor
Download PDF

Keywords

Artificial intelligence
Work reshaping
Verification labor
Three-dimensional structural model
Incentive evolution

DOI

10.26689/pbes.v9i5.15176

Submitted : 2026-05-20
Accepted : 2026-06-04
Published : 2026-06-19

Abstract

Most of the current research on artificial intelligence (AI) and work transformation remains confined to the analytical paradigm of occupational determinism, relying on occupational labels to determine the intensity of AI impact. This approach struggles to effectively explain the significant variations in AI effects across different positions within the same occupation. This paper breaks away from the traditional occupational classification framework and constructs a three-dimensional work structure model based on cognitive demand, structural autonomy, and task interdependence (Cog × Aut × Int). It introduces the core concept of verification labor and employs structured comparative sampling and mixed research methods to conduct a systematic analysis based on 503 questionnaire responses and 20 in-depth interview records. The study elucidates the intrinsic mechanism by which AI drives the transformation of work patterns from execution-dominance to verification and anomaly handling-dominance. The findings reveal that the reshaping of work by AI is not unidirectionally determined by the technology itself but is jointly regulated by the configuration of the three-dimensional work structure. Positions with low cognitive demand and low autonomy exhibit significant execution substitution characteristics, those with medium cognitive demand and medium autonomy demonstrate a coexistence of technological enhancement and job substitution, and positions with high cognitive demand and high autonomy experience a simultaneous increase in performance and identity pressure. Verification labor shows differentiated distribution across various structural contexts, becoming the most representative new form of labor in the AI era. This paper updates and expands the labor process theory to a certain extent, providing a structured perspective and theoretical support for organizations to design work, reconstruct incentive mechanisms, and for individuals to achieve career adaptation.

References

Zheng X, Li L, Gao X, 2023, Configurational Effects of Employee Proactive Behavior: A Process-Based Perspective. Acta Psychologica Sinica, 55(5): 792–811.

Zheng X, Zhang M, 2024, How Enterprises Continuously Activate Employee Work Motivation. Tsinghua Management Review, 2024(7–8): 36–45.

Zheng X, Zhong J, 2024, Where Is Your Career Anchor in the Era of Generative AI? Tsinghua Management Review, 2024(10): 58–67.

Frey C, Osborne M, 2017, The Future of Employment: How Susceptible Are Jobs to Computerization? Technological Forecasting and Social Change, 2017(114): 254–280.

Autor D, 2015, Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives, 29(3): 3–30.

Morgeson F, Humphrey S, 2006, The Work Design Questionnaire (WDQ): Developing and Validating a Comprehensive Measure for Assessing Job Design. Journal of Applied Psychology, 91(6): 1321–1339.