Paper Number
ICIS2025-1206
Paper Type
Short
Abstract
Although AI agents are viewed as “ideal employees” due to their prioritization of organizational interest and submissive nature, organizations face increasing uncertainty about whether employees craft their jobs proactively or passively in response to AI integration. This study proposes that social influence theory offers a useful lens to understand job crafting in human-AI teams, as it explains how implicit cues (e.g., expectations) and explicit cues (e.g., complaints) shape employee behavior. We argue that AI teammates differ from human teammates in two fundamental ways: (1) their lack of self-interest, which limits implicit influence, and (2) their lack of voice, which constrains explicit influence. Drawing on the Theory of Planned Behavior (TPB), we theorize that these characteristics reduce felt obligation and enhance personal control, both of which promote job crafting. We propose two laboratory experiments to test our model. We contribute to extending social influence theory and TPB to human-AI collaboration.
Recommended Citation
Liu, Mandie; Ke, Weiling; and Xu, David (Jingjun), "Is “Ideal Employee” Really Ideal? Effects of AI Agents on Job Crafting Through LESS Felt Obligation and MORE Personal Control" (2025). ICIS 2025 Proceedings. 4.
https://aisel.aisnet.org/icis2025/is_transformwork/is_transformwork/4
Is “Ideal Employee” Really Ideal? Effects of AI Agents on Job Crafting Through LESS Felt Obligation and MORE Personal Control
Although AI agents are viewed as “ideal employees” due to their prioritization of organizational interest and submissive nature, organizations face increasing uncertainty about whether employees craft their jobs proactively or passively in response to AI integration. This study proposes that social influence theory offers a useful lens to understand job crafting in human-AI teams, as it explains how implicit cues (e.g., expectations) and explicit cues (e.g., complaints) shape employee behavior. We argue that AI teammates differ from human teammates in two fundamental ways: (1) their lack of self-interest, which limits implicit influence, and (2) their lack of voice, which constrains explicit influence. Drawing on the Theory of Planned Behavior (TPB), we theorize that these characteristics reduce felt obligation and enhance personal control, both of which promote job crafting. We propose two laboratory experiments to test our model. We contribute to extending social influence theory and TPB to human-AI collaboration.
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