Algorithm and Ancestry: Multi-Level Insights into AI Implementation in Indigenous Tourism

Adoption theories suggest that technological and organizational readiness drive AI use, yet in culturally grounded contexts, adoption often falters. This study explores how service providers in Vietnam’s Indigenous tourism interpret and implement AI. Based on 21 semi-structured interviews across frontline, managerial, and institutional roles, we apply the Technological-Organizational-People (TOP) and Technological-Organizational-Environment (TOE) frameworks to trace multi-level dynamics. Findings reveal that cultural alignment, the fit between AI applications and Indigenous value systems, is both a necessary condition for transforming readiness into legitimate use and a mediating mechanism linking policy and resources to daily practices. AI adoption unfolds through a translation process: frontline actors experiment and adapt, managers verify cultural compatibility, and institutional actors formalize cautious routines. Implementation weakens when technological-cultural misalignment and operational constraints persist. The study extends TOP and TOE by defining when readiness becomes effective and theorizes a multi-level implementation mechanism that legitimizes AI use. These insights guide the design and governance of AI that aligns with Indigenous values while enabling effective service delivery.

Academy of Management Proceedings

Academy of Management Annual Meeting Proceedings

2026

2151-6561

N/A

1

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