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Updated: Apr 9, 2026

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Published on: April 24, 2017
From boost to decline: How AI exposure shapes short-term absorptive-capacity dynamics during onboarding and knowledge
Ci-Rong Li1, Bingyi Lv2, Chunmiao Wang2
1School of Business and Management, Jilin University, China; JLU Research Institute of Innovation and Entrepreneurship, Jilin University, China.
Abstract:
This research examines how AI exposure shapes employees' short-term absorptive-capacity dynamics and knowledge sharing during organizational onboarding. Drawing on self-determination theory, we conceptualize absorptive capacity as a dynamic learning-related capacity characterized by both its initial level and its subsequent trajectory over time. We test this framework in two field studies conducted with onboarding employees in knowledge-intensive firms in Taiwan. Study 1 used a 10-day daily measurement design and latent growth modeling to examine whether AI exposure influenced absorptive capacity and subsequent knowledge-sharing intention. Results showed that AI exposure increased the initial level of absorptive capacity but was associated with a more negative subsequent slope, yielding a positive indirect effect through the intercept and a negative indirect effect through the slope on knowledge-sharing intention. Study 2 replicated and extended this pattern in a three-condition design comparing voluntary AI exposure, mandatory AI exposure, and a control condition, and further examined later behavioral knowledge sharing. The results supported an inverted U-shaped relationship between AI exposure and knowledge-sharing outcomes, such that voluntary AI exposure produced the most favorable pattern. Relative to mandatory exposure, voluntary exposure was associated with a stronger early competence-supporting pathway, a less negative absorptive-capacity trajectory, and higher later behavioral knowledge sharing. Together, these findings show that AI exposure operates not only as a technological condition, but also as a short-term motivational and learning context that shapes how employees engage with knowledge over time. Managerially, the results suggest that the value of AI depends not only on whether employees use it, but also on how that exposure is structured and whether it preserves discretion and sustained self-directed learning during onboarding.
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