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TRUVACE RECORD VERSION
record: TRV-2026-2581
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T07:57:16.340420Z
status: published
lens: trace
sector: business
headline: How Should AI Agents Ask for Donations? Comparison of Emotional and Normative Appeals in AI-Mediated Fundraising
dek: AI chatbots are increasingly being used by charities to engage potential donors. However, as people may exhibit algorithm aversion and heightened scrutiny toward AI, it remains unclear whether persuasive strategies established in human fundraising operate similarly when delivered by an AI agent. In a between-subjects experiment (N=206), participants interacted with a charity AI agent that applied either an emotional appeal (messages evoking compassion and empathy) or a normative appeal (messages emphasizing that…
gain_title: In an experiment with 206 participants, a charity AI agent's compassion-based messages raised donation intentions by inducing empathy.
problem_title: In the same 206-person experiment, the AI agent's "many others donate" messages made the pitch less believable, weakened anticipatory guilt and lowered donation intentions.
trace_subject: Persuasive appeals used by a charity AI agent to solicit donations
gain_reading: In an experiment with 206 participants, a charity AI agent's compassion-based messages raised donation intentions by inducing empathy.
gain_evidence: emotional appeals significantly enhanced donation intentions by inducing empathy
problem_reading: In the same 206-person experiment, the AI agent's "many others donate" messages made the pitch less believable, weakened anticipatory guilt and lowered donation intentions.
problem_evidence: Normative appeals, however, reduced message believability, which subsequently weakened anticipatory guilt and ultimately lowered donation intentions
quick_read: A between-subjects experiment with 206 participants tested how a charity AI agent should ask for money. Each person interacted with an agent that used either an emotional appeal, with messages evoking compassion and empathy, or a normative appeal, stressing that many others donate.

The emotional appeal significantly raised donation intentions by inducing empathy. The normative appeal worked against itself: it reduced how believable the messages were, which weakened anticipatory guilt and ended up lowering donation intentions.

Charities increasingly use AI chatbots to engage potential donors, and the researchers point to algorithm aversion and heightened scrutiny of AI as reasons that tactics proven in human fundraising may not carry over. The results make message believability a boundary condition for AI-delivered normative appeals.
limitation: The finding measures donation intentions, not actual donations, in a single experiment with 206 participants.
tag: Dual reading
key_points: The study was a between-subjects experiment with 206 participants who interacted with a charity AI agent. | One group received emotional appeals evoking compassion and empathy; the other received normative appeals saying many others donate. | Emotional appeals significantly increased donation intentions, with empathy as the mechanism. | Normative appeals lowered message believability, which weakened anticipatory guilt and reduced donation intentions. | The authors identify believability as a critical boundary condition for AI-delivered normative appeals and call for design that calibrates message strategies.
rundown: The research starts from a gap: charities are adopting AI chatbots to engage donors, but it is unclear whether persuasion strategies from human fundraising work the same way when an AI delivers them, given that people may show algorithm aversion and extra scrutiny toward AI.

Participants were split between two conditions. In the emotional condition the agent used messages meant to evoke compassion and empathy. In the normative condition it emphasised that many others donate. Outcomes were donation intentions and the psychological steps leading to them.

Emotional appeals raised donation intentions through empathy. For normative appeals the chain ran the other way: lower believability, then weaker anticipatory guilt, then lower donation intentions. The authors conclude that AI agents soliciting donations need carefully calibrated message strategies.
sources:
- peer_reviewed | International Journal of Human–Computer Interaction | https://doi.org/10.1080/10447318.2026.2719117 | 2026-08-26
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