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

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Authors: Hai‐Jiang Wang, Xuejing Song, Lixin Jiang, Xiaohong Xu, Lirong Long
Cited by: 3
References: 55

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.

Fields of Study & Subjects

Ethics and Social Impacts of AI AI in Service Interactions Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Human Resource Management
Publisher
Wiley
Volume
65
Issue
3
Pages
861–875
Publication date
14 January 2026
Language
EN