過去已有許多探討生成式AI (Generative artificial intelligence, Gen AI)應用於行銷領域的研究，但在非營利組織脈絡中的相關研究仍相對不足。尤其台灣在國際政治的限制，使得台灣非營利組織的研究資料可見性常被忽略。本研究結合上述研究缺口，探討生成式AI介入台灣NGO社群媒體經營時，是否會影響群眾對於貼文的按讚與分享意願，作為往後非營利組織運用AI之參考依據。

本研究採用問卷調查法，以能閱讀中文貼文之Facebook（臉書）且至少每月使用一次的使用者為研究對象，並使用SPSS進行資料分析。研究設計將原始貼文與使用生成式AI改寫修訂之貼文進行比較。研究結果顯示，相較於AI修訂版本，閱聽眾較傾向分享原始貼文內容；且經生成式AI改寫之貼文在理解度上相對較低，進而影響分享意願。此外，若受訪者在一日或單週內曾分享過相似議題之貼文，其分享意願顯著高於30日以上未曾分享者。整體而言，本研究結果顯示生成式AI在內容優化上仍可能存在理解程度差異與傳播效果的限制，並據此提出相關實務建議，以供台灣非營利組織在社群媒體內容撰寫時導入生成式AI的參考依據。

Previous research has extensively examined the application of generative artificial intelligence (Gen AI) in the field of marketing; however, studies focusing on its use within nonprofit organizational contexts remain relatively limited. In particular, due to Taiwan’s constraints in international political participation, research data on Taiwanese nonprofit organizations are often underrepresented in global perception. Addressing these research gaps, this study investigates whether the integration of generative AI into Taiwanese NGOs’ social media practices influences audience intentions to like and share posts, thereby providing insights for the future application of AI in nonprofit communication.
This study employed a survey-based approach, targeting Facebook users who are able to read Chinese-language posts, and analyzed the data using SPSS software. The research design compared original posts with versions revised using generative AI. The results indicate that, compared to AI-revised posts, audiences were more likely to share original content. In addition, posts revised by generative AI were associated with lower levels of perceived understanding, which in turn reduced sharing intentions. Furthermore, respondents who had shared similar content within the past day or week demonstrated significantly higher sharing intentions than those who had not shared similar content in the past 30 days. Overall, the findings suggest that generative AI may still present limitations in terms of message comprehension and diffusion effectiveness when applied to content optimization. Based on these findings, this study offers practical implications for Taiwanese nonprofit organizations seeking to incorporate generative AI into social media content development.

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