TY - GEN
T1 - Domain Expertise and AI Adoption
T2 - 27th International Conference on Enterprise Information Systems, ICEIS 2025
AU - Cao, Guangming
N1 - Publisher Copyright:
© 2025 by Paper published under CC license (CC BY-NC-ND 4.0)
PY - 2025
Y1 - 2025
N2 - The integration of artificial intelligence (AI) offers transformative potential for human resource management (HRM), yet a significant majority of organizations have yet to adopt AI in HRM practices. While much research focuses on individual-level factors in technology adoption, limited attention has been given to the role of domain-specific expertise in shaping HR managers’ perceptions of AI. This study addresses this gap by exploring HR managers’ attitudes and intentions toward AI adoption and examining whether these perceptions differ by gender, job role, organizational size, or industry. Survey data from 279 HR managers in China, analyzed using ANOVA, reveal a largely positive, uniform view of AI adoption, with no significant differences in demographic or organizational factors. These results suggest that shared expertise within HR may drive a cohesive understanding of AI’s benefits, challenging conventional models that emphasize individual or contextual variability in technology adoption. This study contributes to the theoretical framework of technology adoption by highlighting the role of functional expertise in developing uniformity and provides practical insights for designing AI training and implementation strategies that resonate across diverse organizational settings.
AB - The integration of artificial intelligence (AI) offers transformative potential for human resource management (HRM), yet a significant majority of organizations have yet to adopt AI in HRM practices. While much research focuses on individual-level factors in technology adoption, limited attention has been given to the role of domain-specific expertise in shaping HR managers’ perceptions of AI. This study addresses this gap by exploring HR managers’ attitudes and intentions toward AI adoption and examining whether these perceptions differ by gender, job role, organizational size, or industry. Survey data from 279 HR managers in China, analyzed using ANOVA, reveal a largely positive, uniform view of AI adoption, with no significant differences in demographic or organizational factors. These results suggest that shared expertise within HR may drive a cohesive understanding of AI’s benefits, challenging conventional models that emphasize individual or contextual variability in technology adoption. This study contributes to the theoretical framework of technology adoption by highlighting the role of functional expertise in developing uniformity and provides practical insights for designing AI training and implementation strategies that resonate across diverse organizational settings.
KW - Adoption
KW - Artificial Intelligence
KW - Attitude
KW - Domain-Specific Expertise
KW - HR Manager
KW - Intention
UR - https://www.scopus.com/pages/publications/105019503577
U2 - 10.5220/0013232200003929
DO - 10.5220/0013232200003929
M3 - Conference contribution
AN - SCOPUS:105019503577
T3 - International Conference on Enterprise Information Systems, ICEIS - Proceedings
SP - 732
EP - 739
BT - Proceedings of the 27th International Conference on Enterprise Information Systems, ICEIS 2025
A2 - Filipe, Joaquim
A2 - Smialek, Michal
A2 - Brodsky, Alexander
A2 - Hammoudi, Slimane
PB - Science and Technology Publications, Lda
Y2 - 4 April 2025 through 6 April 2025
ER -