Beyond the hype: evidence-based approaches to responsible AI integration in workplace learning

Purpose This paper examines the integration of artificial intelligence (AI) in organizational training and development through an evidence-based lens, addressing the gap between technological enthusiasm and pedagogical effectiveness in workplace learning contexts. Design/methodology/approach An integrative literature review methodology was employed following Torraco’s (2016) framework for synthesizing diverse knowledge streams. The analysis examined 180 papers from multiple databases, combining theoretical frameworks from social cognitive theory (Bandura, 1986) and organizational learning theory (Dittmar et al., 2025) to develop an integrated conceptual framework. Findings The analysis reveals critical misalignments between current AI implementation practices and established learning principles. While AI demonstrates effectiveness in personalized content delivery and routine skill development, significant challenges emerge in supporting transformative learning and maintaining social learning dynamics. Cultural variations and ethical considerations substantially influence implementation success. Originality/value This paper contributes an integrated theoretical framework bridging individual and organizational learning perspectives in AI contexts, identifies specific gaps between technological capabilities and pedagogical requirements and proposes evidence-based guidance for practitioners navigating AI implementation decisions.

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Publication Details

Journal
Education + Training
Published
2025-10-28
DOI
https://doi.org/10.1108/et-01-2025-0034
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Beyond the hype: evidence-based approaches to responsible AI integration in workplace learning

Martin Sposato
Education + Training
Ethics and Social Impacts of AI
article

Beyond the hype: evidence-based approaches to responsible AI integration in workplace learning

Martin Sposato
article en

Abstract

Purpose This paper examines the integration of artificial intelligence (AI) in organizational training and development through an evidence-based lens, addressing the gap between technological enthusiasm and pedagogical effectiveness in workplace learning contexts. Design/methodology/approach An integrative literature review methodology was employed following Torraco’s (2016) framework for synthesizing diverse knowledge streams. The analysis examined 180 papers from multiple databases, combining theoretical frameworks from social cognitive theory (Bandura, 1986) and organizational learning theory (Dittmar et al., 2025) to develop an integrated conceptual framework. Findings The analysis reveals critical misalignments between current AI implementation practices and established learning principles. While AI demonstrates effectiveness in personalized content delivery and routine skill development, significant challenges emerge in supporting transformative learning and maintaining social learning dynamics. Cultural variations and ethical considerations substantially influence implementation success. Originality/value This paper contributes an integrated theoretical framework bridging individual and organizational learning perspectives in AI contexts, identifies specific gaps between technological capabilities and pedagogical requirements and proposes evidence-based guidance for practitioners navigating AI implementation decisions.

Education + TrainingVol. 67(9)
Zayed University (AE)
Openalex Percentile: Top 69%
Ethics and Social Impacts of AI
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