在生成式人工智慧（Gen-AI）蓬勃發展的時代，品牌日益依賴 AI 工具進行行銷內容創作，然而揭露 AI 使用是否會對品牌帶來負面衝擊，仍具學術探討空間。本研究旨在探討在「高涉入產品」情境下，AI 內容揭露對消費者之品牌信任與購買意願的直接影響，並進一步檢視跨文化背景（台灣與美國）以及個體層次變項（AI 熟悉度與知覺風險）的調節效應。本研究採用 2（國家：台灣對美國）× 3（內容情境：AI揭露對AI未揭露對人類創作）的受試者間階乘實驗設計。受試者為來自台灣與美國共 324 名活躍的社群媒體用戶，實驗刺激物則採用模擬的 Instagram 穿戴式科技產品貼文。量化與質性分析結果顯示：第一，對於高涉入產品，明確揭露 AI 參與並不會直接對品牌信任或購買意願產生顯著的直接負面效應，反映出消費者存在「技術適應」與「品質重於來源」的理性評估傾向。第二，不論文化背景為何，AI 生成的內容與人類創作相比，皆會導致消費者購買意願的普遍下滑，顯示出跨文化的「普遍懷疑論」。第三，在調節效應方面，消費者的 AI 熟悉度無法有效緩解 AI 揭露帶來的衝擊；相反地，「知覺風險」發揮了強烈的調節與放大作用，即基準知覺風險較高的消費者，在得知 AI 參與後，其品牌信任與購買意願會出現顯著且更劇烈的跌幅。質性分析進一步證實，台灣消費者對於 AI 揭露多抱持「謹慎中立」態度，關注品牌誠意與去人性化風險；而美國消費者則更為兩極，易引發倫理與透明度方面的強烈反彈。最後，本研究根據上述發現，針對跨國品牌提出了兼顧「脈絡化標籤」與「人機協同」的全球 AI 內容揭露策略架構。

In the era of booming generative artificial intelligence (Gen-AI), brands increasingly rely on AI tools for marketing content creation; however, whether disclosing AI usage brings negative shocks to brands remains academically debated. This study aims to investigate the direct impact of AI content disclosure on consumer brand trust and purchase intention within the context of "high-involvement products," while further examining the moderating effects of cross-cultural backgrounds (Taiwan vs. USA) and individual-level variables (AI familiarity and perceived risk).This study adopts a 2 (Country: Taiwan vs. USA) × 3 (Content Condition: AI-Disclosed vs. AI-Undisclosed vs. Human) between-subjects factorial experimental design. A total of 324 active social media users from Taiwan and the United States participated in the study, with simulated Instagram posts promoting a fictional wearable technology product serving as experimental stimuli.The quantitative and qualitative analyses reveal several critical findings: First, for high-involvement products, explicitly disclosing AI involvement does not exert a significant direct negative impact on either brand trust or purchase intention, reflecting consumers' tendencies toward "technological adaptation" and rational evaluation of "quality over source". Second, regardless of cultural background, AI-generated content consistently leads to a decline in purchase intention compared to human-created content, demonstrating a cross-cultural phenomenon of "universal skepticism". Third, regarding moderating effects, consumers' AI familiarity does not effectively mitigate the shock of AI disclosure. Conversely, "perceived risk" acts as a powerful moderator that amplifies negative outcomes; consumers with higher baseline risk perceptions exhibit a significantly sharper decline in brand trust and purchase intention once AI involvement is revealed. Qualitative analysis further confirms that Taiwanese consumers maintain a "cautious neutrality" toward AI disclosure, focusing on brand sincerity and dehumanization risks, whereas American consumers exhibit more polarized stances, triggering sharper backlash regarding ethics and transparency. Finally, based on these findings, this study proposes a strategic global framework for AI content disclosure that balances "contextual labeling" and "human-in-the-loop" creative approaches for multinational brands.

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