AI-Generated Grant Proposals Create Challenges for Funding Organizations
人工智慧生成的補助申請案為資助機構帶來挑戰
The emergence of AI in grant writing has fundamentally changed the landscape for nonprofits and funding organizations.
AI在補助金撰寫方面的出現，從根本上改變了非營利組織與資助機構的生態。
On one hand, tools allow smaller groups to produce polished, professional proposals, effectively leveling the playing field.
一方面，這些工具讓規模較小的團體也能製作出精煉、專業的提案，有效地平衡了競爭條件。
Because AI often produces generic, "cookie-cutter" content, it is becoming increasingly difficult for funders to identify truly innovative projects.
由於AI經常產出通用的「制式化」內容，資助者越來越難以識別真正具創新性的計畫。
Furthermore, AI models are prone to "hallucinations," where they invent data or citations, which threatens the integrity of the process.
此外，AI模型容易產生「幻覺」，即虛構數據或引用來源，這威脅到了流程的完整性。
Funders are responding by updating policies to mandate transparency, requiring applicants to disclose the use of AI.
資助者透過更新政策來強制要求透明度，要求申請者揭露AI的使用情形。
Many organizations are now shifting their focus toward more complex, reflective questions that require deep institutional knowledge, which AI struggles to mimic.
許多組織現在將焦點轉向更複雜、需反思的問題，這些問題需要深厚的機構知識，而這正是AI難以模仿的。
Ultimately, the best practice is a human-AI hybrid approach.
歸根結底，最佳實踐是「人機協作」的模式。
AI should be used for administrative efficiency—such as formatting or drafting routine sections—but final proposals must be verified by humans.
AI應被用於行政效率（如格式調整或起草例行性段落），但最終提案必須由人工核實。
By focusing AI on tedious tasks, nonprofits can reclaim time for what matters most: building authentic, personal relationships with funders to demonstrate their mission’s genuine impact.
透過將AI用於繁瑣任務，非營利組織可以節省時間投入到最重要的事情上：與資助者建立真誠、個人的關係，以展示其使命的真實影響力。
