More flow and less objectification: Dual influence mechanisms of generative AI use on employees’ proactive behaviors

A three-wave, time-lagged survey of 380 full-time knowledge workers found that greater use of generative artificial intelligence was associated with more proactive employee behavior, according to the study abstract. The researchers modeled two possible pathways: flow experience, described as the “empowering humans” pathway, and workplace objectification, described as the “liberating humans” pathway.

Generative AI use was associated with stronger flow experiences and lower workplace objectification. Each factor partially mediated the relationship between generative AI use and proactive behavior, indicating that the survey analysis identified both an association with the quality of employees’ work experience and an association with reduced objectification. These results are consistent with the study’s dual-pathway framework, but the abstract does not provide enough methodological detail to determine how each variable was measured or how robust the mediation results were.

Digital literacy showed an asymmetrical moderating effect. It strengthened the negative relationship between generative AI use and workplace objectification, as well as the corresponding indirect relationship with proactive behavior. Its moderating effect on the relationship between generative AI use and flow experience was not statistically significant. In other words, the reported statistical models supported a moderation result for the objectification pathway but not for the flow pathway.

The evidence comes from a survey of full-time knowledge workers analyzed with mediation and moderation models, not from an experiment or another design capable of establishing causal effects. The supplied abstract does not specify recruitment procedures, the organizational or national setting, the measures used for proactive behavior, or possible unmeasured confounding. It also does not report effect sizes, confidence intervals, attrition across the three waves, robustness checks, or details relevant to generalizability. Because only the abstract was supplied, this report summarizes the accepted research as described there and does not independently assess the full study, its instruments or statistical analyses. The findings should therefore be interpreted as associations observed among the surveyed knowledge workers rather than demonstrated causal effects of generative AI use.

Subject of Research: Survey analysis of how generative AI use is associated with employee proactive behavior, flow, workplace objectification, and digital literacy.

Article Title: More flow and less objectification: Dual influence mechanisms of generative AI use on employees’ proactive behaviors

Article References: Xu, S., Mei, Y., Yao, K., Wang, R., & Zhong, J. (2026). More flow and less objectification: Dual influence mechanisms of generative AI use on employees’ proactive behaviors. BMC Psychology. https://doi.org/10.1186/s40359-026-05643-7

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05643-7

Keywords: generative artificial intelligence, employee proactive behavior, flow experience, workplace objectification, digital literacy, knowledge workers, time-lagged survey, mediation analysis, moderation analysis, flow, less, objectification