Paper Number
ICIS2025-2038
Paper Type
Short
Abstract
As organizations expand AI-enabled operations across diverse markets, balancing global scalability with cultural adaptation emerges as a strategic challenge. This study examines synthetic data to advance glocalization and strengthens AI orientation within firms. Drawing on Dynamic Capabilities Theory and Socio-Technical Systems Theory, we develop a conceptual model in which glocalization mediates the influence of synthetic data on AI orientation, moderated by interoperability and cultural fluency. Synthetic data is positioned as a strategic resource that enables the creation of culturally and legally compliant datasets. Interoperability ensures seamless integration of synthetic datasets across infrastructures, while cultural fluency enhances the authenticity and acceptance of localized AI systems. Using a mixed-methods approach, we propose conducting qualitative interviews with CEOs, CIOs and other higher officials of technology-based organizations and three quantitative studies to test the propositions. Our findings will offer strategic insights into how synthetic data can support culturally adaptive, globally scalable AI deployment.
Recommended Citation
Avik, Suranjeet Chowdhury, "Glocalization in The AI Era: How Synthetic Data Bridges Technical and Cultural Divides" (2025). ICIS 2025 Proceedings. 22.
https://aisel.aisnet.org/icis2025/gen_ai/gen_ai/22
Glocalization in The AI Era: How Synthetic Data Bridges Technical and Cultural Divides
As organizations expand AI-enabled operations across diverse markets, balancing global scalability with cultural adaptation emerges as a strategic challenge. This study examines synthetic data to advance glocalization and strengthens AI orientation within firms. Drawing on Dynamic Capabilities Theory and Socio-Technical Systems Theory, we develop a conceptual model in which glocalization mediates the influence of synthetic data on AI orientation, moderated by interoperability and cultural fluency. Synthetic data is positioned as a strategic resource that enables the creation of culturally and legally compliant datasets. Interoperability ensures seamless integration of synthetic datasets across infrastructures, while cultural fluency enhances the authenticity and acceptance of localized AI systems. Using a mixed-methods approach, we propose conducting qualitative interviews with CEOs, CIOs and other higher officials of technology-based organizations and three quantitative studies to test the propositions. Our findings will offer strategic insights into how synthetic data can support culturally adaptive, globally scalable AI deployment.
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