Human vs. Machine: A Pygmalion Perspective on Anthropomorphism and the Effectiveness of <scp>AI</scp> Feedback for Individual Learning

ABSTRACT Despite the widespread adoption of artificial intelligence (AI) in human resource management (HRM) practices, developmental feedback provided by AI does not always achieve its intended effectiveness. Drawing on the Pygmalion theory and the literature on human‐AI interactions, we propose that individuals perceive lower expectation when AI provides developmental feedback, compared to human feedback providers. Perceived expectation positively influences individual learning (i.e., learning motivation and learning performance) and mediates the relationship between feedback provider (human vs. AI) and individual learning. Furthermore, we propose that feedback recipients may perceive higher expectation from anthropomorphic (vs. non‐anthropomorphic) AI, leading to greater learning outcomes. Our findings provide support for these predictions through two scenario‐based experiments (Studies 1 and 2) and a field experiment (Study 3) across a variety of learning contexts. This research sheds new light on the underlying mechanisms of human‐AI interaction and offers practical implications for organizations seeking to utilize AI technology more effectively in employee learning and development.

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Publication Details

Journal
Human Resource Management
Published
2026-01-14
DOI
https://doi.org/10.1002/hrm.70053
Citations
2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
51.30
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article

Human vs. Machine: A Pygmalion Perspective on Anthropomorphism and the Effectiveness of AI Feedback for Individual Learning

Xiaohong Xu, Lirong Long, Hai‐Jiang Wang, Lixin Jiang et al.
2 citations
Human Resource Management
Ethics and Social Impacts of AI
51.30
article

Human vs. Machine: A Pygmalion Perspective on Anthropomorphism and the Effectiveness of AI Feedback for Individual Learning

Xiaohong Xu, Lirong Long, Hai‐Jiang Wang, Lixin Jiang, Xuejing Song
article en
2 citations

Abstract

ABSTRACT Despite the widespread adoption of artificial intelligence (AI) in human resource management (HRM) practices, developmental feedback provided by AI does not always achieve its intended effectiveness. Drawing on the Pygmalion theory and the literature on human‐AI interactions, we propose that individuals perceive lower expectation when AI provides developmental feedback, compared to human feedback providers. Perceived expectation positively influences individual learning (i.e., learning motivation and learning performance) and mediates the relationship between feedback provider (human vs. AI) and individual learning. Furthermore, we propose that feedback recipients may perceive higher expectation from anthropomorphic (vs. non‐anthropomorphic) AI, leading to greater learning outcomes. Our findings provide support for these predictions through two scenario‐based experiments (Studies 1 and 2) and a field experiment (Study 3) across a variety of learning contexts. This research sheds new light on the underlying mechanisms of human‐AI interaction and offers practical implications for organizations seeking to utilize AI technology more effectively in employee learning and development.

Human Resource Management
University of Auckland (NZ), Peking University (CN), The University of Texas at San Antonio (US), Huazhong University of Science and Technology (CN)
Decent work and economic growth
Openalex Percentile: Top 1%
Ethics and Social Impacts of AI
51.30
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