TY  - JOUR
T1  - Modeling the Impact of Artificial Intelligence Adoption on Employee Behavioral Adaptation and Organizational Resilience: A Structural Equation Modeling Approach
A1  - Felix-Henry Gutierrez-Castillo
A1  - Bertelly Turpo-Aliaga
A1  - Delia-Concepción Cahuana-Pacco
A1  - Yethy-Melixa Poma-Palma
A1  - Rómulo Huacasi-Gonzales
A1  - Litzbel Charaja-Fernandez
A1  - Alejandro Ticona-Machaca
JF  - Journal of Organizational Behavior Research
JO  - J Organ Behav Res
SN  - 2528-9705
Y1  - 2026
VL  - 11
IS  - 1
DO  - 10.51847/yY7evdtzAy
SP  - 207
EP  - 217
N2  - This study examines how artificial intelligence adoption may influence organizational resilience through employee behavioral adaptation. The article develops and tests a mediation model in which AI adoption supports adaptive employee behaviors, including skill acquisition, role flexibility, and proactive problem-solving. Organizational resilience is conceptualized as the combined capacity to anticipate disruptions, respond with agility, and recover operational continuity. An empirical survey dataset comprising 350 employees from AI-adopting organizations was used to test the proposed model. The study applies structural equation modeling to evaluate the measurement model, structural relationships, and indirect effect. The empirical design provides field-based evidence on the relationships among AI adoption, employee behavioral adaptation, and organizational resilience. The findings indicate that AI adoption is positively associated with employee behavioral adaptation. Employee behavioral adaptation is also positively associated with organizational resilience. The direct relationship between AI adoption and organizational resilience becomes non-significant when employee behavioral adaptation is included, indicating full mediation in the empirical model. The study contributes to organizational behaviour and technology adoption research by clarifying the behavioural mechanism through which AI implementation may translate into resilience capability. It suggests that AI systems do not automatically produce resilient organizations; rather, resilience emerges when employees learn, adjust, and proactively reconfigure work practices around new technological possibilities. This perspective positions employee adaptation as a central explanatory link between digital transformation and organizational outcomes. The study is limited by its cross-sectional design and reliance on survey-based self-reported data. Future research should test the proposed model using longitudinal, multi-source, and cross-cultural datasets. Despite these limitations, the article offers a theoretically grounded and statistically coherent SEM framework for examining AI adoption, employee adaptation, and organizational resilience using empirical organizational data.
UR  - https://odad.org/article/modeling-the-impact-of-artificial-intelligence-adoption-on-employee-behavioral-adaptation-and-organi-gipos5dl63zq9kh
ER  -