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How can organizations improve hiring practices with AI? An examination of predictors of AI acceptance in hiring and recruitment

Ying Xiong et al.

Journal of Communication Management2026https://doi.org/10.1108/jcom-02-2025-0043article
AJG 1ABDC B
Weight
0.50

Abstract

Purpose Artificial intelligence (AI) has been used in employee recruitment through resume screening, interviewing, and decision-making in recent years. Communicating with job candidates about the use of AI is crucial for organizations’ hiring practices. The study examines the predictors of AI acceptance and objection in the AI-driven hiring process and explores the role of anxiety in AI technology’s acceptance. Design/methodology/approach We conducted an online survey (N = 463) to explore the predictors of individuals’ AI technology acceptance and objection in hiring by employing the AI device use acceptance (AIDUA) model. Structural equation modeling was used to test the proposed model. Findings Social influence, hedonic motivation, and novelty are positively associated with performance expectancy, while anthropomorphism is positively associated with effort expectancy. Performance expectancy directly impacts individuals’ acceptance of AI use in hiring as well as objection to using AI in hiring. The relationship between effort expectancy and behavioral intentions was mediated by anxiety without significant direct effects. Practical implications The important role of anxiety in shaping individuals’ acceptance and objection to AI technology in hiring suggests that organizations should aim to reduce job candidates’ negative emotions associated with using AI technologies. The significant role of performance expectancy highlights the need for organizational practitioners to emphasize the perceived benefits of AI. Originality/value This study offers valuable insights into the role of emotions in shaping individuals’ acceptance of AI in hiring processes and highlights the necessity of effective AI communication to increase job candidates’ acceptance of AI use in hiring. By extending the AIDUA model, the findings contribute to the theoretical understanding of AI adoption and rejection while providing practical strategies for communication management practitioners.

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https://doi.org/https://doi.org/10.1108/jcom-02-2025-0043

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@article{ying2026,
  title        = {{How can organizations improve hiring practices with AI? An examination of predictors of AI acceptance in hiring and recruitment}},
  author       = {Ying Xiong et al.},
  journal      = {Journal of Communication Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/jcom-02-2025-0043},
}

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How can organizations improve hiring practices with AI? An examination of predictors of AI acceptance in hiring and recruitment

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.