Abstract—This study investigates how privacy concerns influence public trust and adoption of online Generative AI (GenAI) services, specifically comparing western (e.g., ChatGPT) and non-western (e.g., DeepSeek) services. A national cross-sectional survey was conducted across diverse demographics, exploring privacy risks related to both online purchasing and Online GenAI Services usage. This research fills a knowledge gap by specifically examining public perception of privacy protection across western versus non-western Online GenAI Services. To accomplish that we introduce a new index named Adoption-to-Concern Ratio (ACR). Findings indicate that public privacy concern for western Online GenAI Services is moderate, yielding relatively high adoption willingness. Concern intensifies significantly for non-western services, including foreign government exploitation and unintended data use. This translates to significantly reduced willingness to adopt non-western services. While price reduction modestly promotes adoption, superior quality/accuracy is a more effective driver for non-western Online GenAI Services. Non-western developers must build trust through transparency and demonstrate superior quality, not just lower cost. Western providers need more active measures beyond legal compliance to maintain trust. Growing concerns with AI privacy affect public trust and adoption and they manifest in geopolitical tensions around data sovereignty and ethical dilemmas about IP.

Keywords—online services, privacy, Generative Artificial Intelligence (GenAI), AI risks

Cite: Amir Schreiber and Ilan Schreiber, "From Concern to Trust: How Privacy Shapes Public Adoption of Western Versus Non-Western Online GenAI Services," Journal of Advanced Management Science, Vol. 14, No. 1, pp. 24-39, 2026.