Analytical model of the relationship between language barriers and knowledge processing and artificial intelligence

Document Type : Original Article

Authors

Assistant Professor, Department of Public Management, Payame Noor University, Tehran, Iran

Abstract

Purpose: This study aims to present an analytical model examining the relationship between language barriers (comprising translation barriers, linguistic complexity, and cultural adaptation barriers) and organizational knowledge processing, with a specific focus on the mediating role of artificial intelligence (AI) within the export storage units of the Shazand and Mahshahr petrochemical companies. The research addresses the growing importance of knowledge management and the application of emerging AI technologies in multicultural and multilingual business environments.
Methodology: This applied study employs a descriptive-survey design and is causal (ex post facto) in nature. The statistical population comprised all employees of the export storage units of the Shazand and Mahshahr petrochemical companies ($N = 70$), who were selected via a census method. Data were collected using three standardized questionnaires: a language barrier questionnaire (21 items across 3 dimensions), a knowledge processing questionnaire (7 items across 2 dimensions), and an AI questionnaire (22 items across 5 dimensions). Validity was confirmed by expert review, and reliability was established with Cronbach's alpha coefficients exceeding 0.7. Data were analyzed using confirmatory factor analysis and structural equation modeling (SEM) via the partial least squares (PLS) approach.
Findings: The results indicate that all dimensions of language barriers (translation barriers, linguistic complexity, and cultural adaptation barriers) exert a significant effect on organizational knowledge processing. Moreover, AI plays a mediating role in these relationships, with the strongest mediation observed between translation barriers and knowledge processing (path coefficient = 0.991). This suggests that a portion of the impact of language barriers on knowledge processing is transmitted through AI, which effectively helps mitigate the adverse effects of these barriers.
Conclusion: These findings underscore the importance of accurate translation, plain language usage, culturally adaptive content, and AI adoption in enhancing knowledge processing within organizations. AI facilitates the knowledge transfer process—particularly in specialized and multilingual settings—by reducing communication hurdles. Consequently, managers should focus not only on addressing language barriers but also on developing the necessary infrastructure for AI integration and providing adequate staff training to optimize technology utilization.

Keywords

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References

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Sciences and Techniques of Information Management
Volume 12, Issue 2
June 2026
Pages 126-142

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