同化(音韵学)
业务
计算生物学
药理学
生物
哲学
语言学
作者
Maryam Hina,Nasreen Azad,A.K.M. Najmul Islam
出处
期刊:Information Technology & People
[Emerald (MCB UP)]
日期:2025-03-20
卷期号:38 (8): 73-96
被引量:2
标识
DOI:10.1108/itp-06-2024-0808
摘要
Purpose Most prior studies have primarily investigated AI adoption, with less attention given to AI assimilation in human resource management (HRM). Additionally, prior studies often lack empirical verification of the extent to which human–AI collaboration might alleviate challenges and promote AI assimilation in the HRM context. Thus, this study aims to explore AI assimilation in recruitment with a balanced view that identifies both enabling and inhibiting factors while examining the role of human–AI collaboration in mitigating the effects of inhibiting factors. Design/methodology/approach We used a mixed-method approach. Using an open-ended survey questionnaire approach and collecting data from 26 HR professionals, we identified five factors, namely, AI competency, recruitment agility, AI opacity, AI empathy and human–AI collaboration, potentially impacting AI assimilation. Thereafter, drawing from the enabler–inhibitor perspective, we theorize that AI competency and recruitment agility are the enablers, whereas AI opacity and AI empathy are the inhibitors of an organization’s efforts to assimilate AI in recruitment practices. We tested our proposed model by collecting data from 309 HR professionals. Findings The findings showed that both enablers, AI competency and recruitment agility, significantly influence AI assimilation; however, both inhibitors, AI opacity and AI empathy, are non-significant for AI assimilation. While looking into the reasons for these non-significant effects, we observed that the interaction term between AI empathy and human–AI-collaboration as well as between AI opacity and human–AI-collaboration both had significant effects on AI assimilation. These interaction effects suggest that human–AI collaboration mitigates the constraining impact of both inhibitors. Originality/value Drawing from the enabler–inhibitor perspective and by empirically testing our proposed model, this paper significantly contributes to the IS literature. Our study not only identifies factors that promote and inhibit AI assimilation in the context of HRM practices but also reveals how human–AI collaboration may mitigate the effects of inhibitors. Our findings suggest that organizations should have a collaborative recruitment environment where AI handles repetitive tasks, and humans focus on roles requiring emotional intelligence. This approach enhances the integration of AI-powered tools, addresses AI assimilation inhibitors and optimizes recruitment effectiveness.
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