Artificial intelligence readiness in management education: Scale development and validation

Given the proliferation of artificial intelligence (AI) technology, there is a need for management education academics and practitioners to develop an effective and reliable instrument to assess individual readiness to adapt and embrace AI technology/products. The purpose of this study is to develop and validate an artificial intelligence readiness scale (AIRS) with good psychometric properties. The procedures used in conceptualizing the AIRS construct, generating items, collecting data, and validating the multiple-item scale are described. This study provides evidence of reliability, content validity, criterion-related validity, convergent validity, discriminant validity, and nomological validity by analyzing data from a sample of 174 respondents from different industries. Based on the analysis results, a 13-item AIRS with four dimensions (i.e., self-efficacy and cognition, optimism, collaborative learning and working, and comfort) is developed and validated. A tentative norm of the AIRS is also presented. The proposed AIRS provides several important theoretical and practical implications for developing AI-related management education theories and promoting the usage of AI-based products/educational technology. • The study develops and validates an artificial intelligence readiness scale (AIRS). • The scale contains 13 items representing four dimensions. • The scale can be used to assess individuals' artificial intelligence readiness in the context of management education.

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Publication Details

Journal
The International Journal of Management Education
Published
2026-04-25
DOI
https://doi.org/10.1016/j.ijme.2026.101429
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial intelligence readiness in management education: Scale development and validation

Yi‐Shun Wang, I-Ying Wang, Wen-Hsien Lai, Cheng-Yu Hung et al.
The International Journal of Management Education
AI in Service Interactions
article

Artificial intelligence readiness in management education: Scale development and validation

Yi‐Shun Wang, I-Ying Wang, Wen-Hsien Lai, Cheng-Yu Hung, Hsin-Hui Lin
article en

Abstract

Given the proliferation of artificial intelligence (AI) technology, there is a need for management education academics and practitioners to develop an effective and reliable instrument to assess individual readiness to adapt and embrace AI technology/products. The purpose of this study is to develop and validate an artificial intelligence readiness scale (AIRS) with good psychometric properties. The procedures used in conceptualizing the AIRS construct, generating items, collecting data, and validating the multiple-item scale are described. This study provides evidence of reliability, content validity, criterion-related validity, convergent validity, discriminant validity, and nomological validity by analyzing data from a sample of 174 respondents from different industries. Based on the analysis results, a 13-item AIRS with four dimensions (i.e., self-efficacy and cognition, optimism, collaborative learning and working, and comfort) is developed and validated. A tentative norm of the AIRS is also presented. The proposed AIRS provides several important theoretical and practical implications for developing AI-related management education theories and promoting the usage of AI-based products/educational technology. • The study develops and validates an artificial intelligence readiness scale (AIRS). • The scale contains 13 items representing four dimensions. • The scale can be used to assess individuals' artificial intelligence readiness in the context of management education.

The International Journal of Management EducationVol. 24(3)
National Taichung University of Science and Technology (TW), National Changhua University of Education (TW)
National Science and Technology Council
Openalex Percentile: Top 4%
AI in Service Interactions
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