International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 2
March-April 2026
Indexing Partners
Artificial Intelligence in Cross-cultural Leadership Hiring: Reducing Bias and Improving Global Leadership Fit
| Author(s) | Sonakshi Srivastava |
|---|---|
| Country | India |
| Abstract | Globalization has compelled organizations to recruit leaders across national and cultural boundaries, increasing the complexity of leadership selection. Cultural differences in communication, authority perception, decision-making, and emotional expression often lead to biased evaluations and poor hiring outcomes. Artificial Intelligence (AI) has emerged as a transformative tool in talent acquisition, offering data-driven assessment, pattern recognition, and bias reduction. This paper develops a comprehensive conceptual and analytical framework explaining how AI can improve leadership hiring across cultural barriers. Drawing on cross-cultural leadership theory, cultural intelligence (CQ), and AI-enabled recruitment research, the study proposes a model linking AI assessment systems, cultural distance, and leadership success. Simulated analytical results illustrate how AI prediction accuracy moderates the negative effect of cultural distance on leadership outcomes. The findings suggest AI enhances objectivity, identifies transferable leadership traits, and supports culturally adaptive evaluation. However, AI systems must be culturally trained and ethically governed to avoid algorithmic bias. The study offers implications for international HR management, leadership development, and AI governance, and provides a roadmap for organizations seeking to build culturally competent global leadership pipelines. |
| Keywords | Artificial Intelligence, Leadership Hiring, Cultural Barriers, Cultural Intelligence, Global Talent Management, HR Analytics. |
| Published In | Volume 8, Issue 1, January-February 2026 |
| Published On | 2026-02-13 |
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E-ISSN 2582-2160
CrossRef DOI is assigned to each research paper published in our journal.
IJFMR DOI prefix is
10.36948/ijfmr
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