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TRUVACE RECORD VERSION
record: TRV-2026-2696
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:02:08.728422Z
status: published
lens: g_space
sector: labor
headline: AI ‐Enabled Performance Feedback Design: The Effects of Anthropomorphic AI Feedback Source, Feedback Valence and Emotional Arousal on Employee Advice‐Taking Behaviour
dek: ABSTRACT Companies are increasingly using artificial intelligence (AI) to provide employees with performance feedback, but its efficacy is inconsistent. Drawing upon the theories of mind perception and feedback intervention, we examine the effects of anthropomorphic AI feedback source and feedback valence in conveying performance feedback on employees' advice‐taking behaviours. We conducted a 2 × 2 experiment in which we manipulated anthropomorphic AI feedback source (more versus less) and examined how feedback…
gain_title: In a 2×2 experiment using skin-conductance sensors during a production task, employees who got positive feedback from a more human-like AI showed higher emotional arousal and took more advice afterward than those who got it from a less human-like AI.
problem_title: (none)
trace_subject: (none)
gain_reading: In a 2×2 experiment using skin-conductance sensors during a production task, employees who got positive feedback from a more human-like AI showed higher emotional arousal and took more advice afterward than those who got it from a less human-like AI.
gain_evidence: receiving positive feedback from a more anthropomorphic AI instead of a less anthropomorphic counterpart results in higher emotional arousal, which leads to more subsequent advice‐taking behaviour
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers ran a 2×2 experiment on how employees respond when an AI system gives them performance feedback. They varied how human-like the AI feedback source was and whether the feedback was positive or negative, then measured advice-taking in a production task.

Positive feedback from the more human-like AI produced higher emotional arousal, recorded with an electrodermal activity device, and more advice-taking afterward than positive feedback from the less human-like AI.

With negative feedback, arousal and advice-taking did not differ between the more and less human-like AI. The result points to emotional language mattering most when feedback is favourable, as companies roll out AI feedback tools with uneven results.
limitation: The human-like AI advantage appeared only for positive feedback; under negative feedback, arousal and advice-taking did not differ between the AI types.
tag: Evidence-backed gain
key_points: The experiment crossed two factors: a more versus less human-like AI feedback source and positive versus negative feedback. | Emotional arousal was measured with an electrodermal activity device while employees did a production task. | Positive feedback from a more human-like AI led to higher arousal and more advice-taking than from a less human-like AI. | With negative feedback, arousal and advice-taking were the same for both AI types. | The authors draw on mind perception and feedback intervention theories to explain the pattern.
rundown: The study starts from the observation that companies increasingly use AI to give employees performance feedback, but that its effectiveness is inconsistent. It tests whether making the AI source seem more human changes how employees react.

Participants did a production task and received feedback from either a more or a less anthropomorphic AI. Skin-conductance readings captured emotional arousal, and later advice-taking behaviour was the outcome of interest.

The authors report that the human-like source only made a difference for positive feedback, where it raised arousal and advice-taking. They frame this as evidence for the role of emotional language in feedback delivered by anthropomorphic AI systems.
sources:
- peer_reviewed | Accounting & Finance | https://doi.org/10.1111/acfi.70228 | 2026-05-15
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