Jul 2026· Frontiers in Human Dynamics· Vol 8· 1 citation· 104 references
TL;DR
Examination of HRM-related AI readiness factors relates to four AI readiness components supports conceptualizing AI readiness as a human-centered, multidimensional organizational capability and suggests that capability building through “HR development”, supported by leadership and targeted change practices, may help strengthen AI readiness for AI-enabled change in public administration.
Abstract
Public administration increasingly relies on artificial intelligence (AI) to optimize processes, personalize services, and improve decision-making; however, evidence on human resources management (HRM) for AI readiness remains limited. This article examines how six HRM-related AI readiness factors relate to four AI readiness components (“Adaptability”, “Proactivity”, “Resilience”, “Ethical governance commitment”), with human resources (HR) development as a central capability-building lever. Data were collected through an online survey of 112 senior public managers in Slovenia conducted between May and July 2025 and analyzed using partial least squares structural equation modeling (PLS-SEM) to test the direct relationships between HRM factors and AI readiness components. “Human resources (HR) development” is the only factor positively associated with all AI readiness components, but the findings are exploratory due to modest effect sizes, low reliability for some constructs, and limited discriminant validity. “Leadership style” is associated with “Resilience” and “Ethical governance commitment,” while “Change management” shows a smaller association with “Proactivity.” Factors such as “HR planning, recruiting, hiring,” “Communication and collaboration,” and “Organizational culture” do not show statistically significant direct associations in the tested model. The findings support conceptualizing AI readiness as a human-centered, multidimensional organizational capability and suggest that capability building through “HR development”, supported by leadership and targeted change practices, may help strengthen AI readiness for AI-enabled change in public administration.
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