Learning to work with artificial intelligence: workplace learning and capability development among HR professionals

Purpose This study aims to examine how human resource (HR) professionals develop learning readiness for artificial intelligence (AI) in their work and the barriers and professional development processes that shape this capability in AI-enabled HR contexts. Design/methodology/approach A qualitative research design was adopted based on 17 semi-structured interviews with HR professionals selected through purposive sampling. Data were analysed using the Gioia methodology enabling a systematic inductive analysis through first-order concepts, second-order themes and aggregate dimensions to capture how HR professionals experience learning readiness for AI. Participants engaged with a range of AI technologies, including generative AI and large language models, predictive HR analytics and automation and HR information systems, which entailed distinct learning demands. Findings Learning readiness for AI emerges primarily as a practice-based learning capability developed through engagement with HR work rather than through formal preparation. Barriers to learning are predominantly organisational, including limited time, lack of strategic direction and insufficient institutional support. HR professionals value contextual and interpretive learning approaches over highly technical training, highlighting the importance of professional judgement when working with AI-generated outputs. Research limitations/implications Based on a qualitative sample within a specific national context, the findings cannot be generalised broadly. However, the study contributes to HR development research by showing how learning readiness for AI develops through workplace learning processes and how organisational conditions shape the development of professional capabilities in technologically mediated work environments. Practical implications Organisations should approach AI readiness as an ongoing, practice-based developmental process rather than as a competence achieved through formal training alone. The findings suggest that creating structured opportunities for experimentation, peer interaction and reflection within everyday work is essential to support capability development. In addition, organisations need to provide clearer strategic direction, protected time for learning and formal recognition of AI-related development to enable HR professionals to build the interpretive and judgement-based capabilities required in AI-enabled work environments. Originality/value The study provides qualitative evidence on how HR professionals experience learning for AI in practice. It contributes to the literature by linking AI-driven changes in HR work with human capital development and workplace learning processes. Furthermore, it theorises that learning readiness for AI is a capability produced through relationships rather than a pre-existing competence.

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Publication Details

Journal
European journal of training and development
Published
2026-08-24
DOI
https://doi.org/10.1108/ejtd-03-2026-0065
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Learning to work with artificial intelligence: workplace learning and capability development among HR professionals

Elena Rivo-López, Mónica Villanueva-Villar, Fernando Arístegui Monge
European journal of training and development
Ethics and Social Impacts of AI
article

Learning to work with artificial intelligence: workplace learning and capability development among HR professionals

Elena Rivo-López, Mónica Villanueva-Villar, Fernando Arístegui Monge
article en

Abstract

Purpose This study aims to examine how human resource (HR) professionals develop learning readiness for artificial intelligence (AI) in their work and the barriers and professional development processes that shape this capability in AI-enabled HR contexts. Design/methodology/approach A qualitative research design was adopted based on 17 semi-structured interviews with HR professionals selected through purposive sampling. Data were analysed using the Gioia methodology enabling a systematic inductive analysis through first-order concepts, second-order themes and aggregate dimensions to capture how HR professionals experience learning readiness for AI. Participants engaged with a range of AI technologies, including generative AI and large language models, predictive HR analytics and automation and HR information systems, which entailed distinct learning demands. Findings Learning readiness for AI emerges primarily as a practice-based learning capability developed through engagement with HR work rather than through formal preparation. Barriers to learning are predominantly organisational, including limited time, lack of strategic direction and insufficient institutional support. HR professionals value contextual and interpretive learning approaches over highly technical training, highlighting the importance of professional judgement when working with AI-generated outputs. Research limitations/implications Based on a qualitative sample within a specific national context, the findings cannot be generalised broadly. However, the study contributes to HR development research by showing how learning readiness for AI develops through workplace learning processes and how organisational conditions shape the development of professional capabilities in technologically mediated work environments. Practical implications Organisations should approach AI readiness as an ongoing, practice-based developmental process rather than as a competence achieved through formal training alone. The findings suggest that creating structured opportunities for experimentation, peer interaction and reflection within everyday work is essential to support capability development. In addition, organisations need to provide clearer strategic direction, protected time for learning and formal recognition of AI-related development to enable HR professionals to build the interpretive and judgement-based capabilities required in AI-enabled work environments. Originality/value The study provides qualitative evidence on how HR professionals experience learning for AI in practice. It contributes to the literature by linking AI-driven changes in HR work with human capital development and workplace learning processes. Furthermore, it theorises that learning readiness for AI is a capability produced through relationships rather than a pre-existing competence.

European journal of training and developmentVol. 50(10)
Universidade de Vigo (ES)
Openalex Percentile: Top 6%
Ethics and Social Impacts of AI
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