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<p>Charitable organizations increasingly turn to artificial intelligence tools to address the challenge of soliciting charitable donations. However, unlike in corporate contexts, the use of AI in charitable settings may signal extrinsic motives (e.g., cost reduction or efficiency gains) rather than the genuine altruistic intent donors expect, ultimately reducing donor engagement. A field experiment on Facebook revealed significantly lower click-through rates for AI-labeled charitable advertisements (N = 118,927). Controlled experiments (Studies 2–3, N = 761) confirmed this negative effect and showed that charitable AI usage heightens perceptions of extrinsic organizational motivation while diminishing perceived authenticity—sequential mediators that explain reduced charitable giving. Study 4 (N = 599) demonstrated that when charitable AI usage is framed around intrinsic motivations, the observed negative effects are attenuated. Crucially, entity type moderates this phenomenon: Corporations avoid backlash for charitable AI usage, whereas nonprofits experience significantly greater negative effects (Study 5, N = 995). These findings introduce a novel motivational perspective to AI adoption research and provide actionable guidelines for organizations adopting AI technology in charitable activities.</p>

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AI’s Hidden Price: AI Tools Reduce Donor Engagement Through Extrinsic Motivation Inferences

  • 期刊论文

  • 发表日期：

    2026年1月21日

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  • Yujie Zhao,
  • Pete Pengcheng Zhou,
  • Zengxiang Chen

摘要

Charitable organizations increasingly turn to artificial intelligence tools to address the challenge of soliciting charitable donations. However, unlike in corporate contexts, the use of AI in charitable settings may signal extrinsic motives (e.g., cost reduction or efficiency gains) rather than the genuine altruistic intent donors expect, ultimately reducing donor engagement. A field experiment on Facebook revealed significantly lower click-through rates for AI-labeled charitable advertisements (N = 118,927). Controlled experiments (Studies 2–3, N = 761) confirmed this negative effect and showed that charitable AI usage heightens perceptions of extrinsic organizational motivation while diminishing perceived authenticity—sequential mediators that explain reduced charitable giving. Study 4 (N = 599) demonstrated that when charitable AI usage is framed around intrinsic motivations, the observed negative effects are attenuated. Crucially, entity type moderates this phenomenon: Corporations avoid backlash for charitable AI usage, whereas nonprofits experience significantly greater negative effects (Study 5, N = 995). These findings introduce a novel motivational perspective to AI adoption research and provide actionable guidelines for organizations adopting AI technology in charitable activities.