Employee resilience under AI disruption: the mediating role of perceived organizational support & moderating effects of ethical leadership and career stage

Purpose This paper examines how artificial intelligence (AI) disruption influences employee resilience, with particular attention to the heightened vulnerability of mid-career employees. It develops a five-proposition conceptual framework that positions perceived organizational support (POS) as the central mediating mechanism and ethical leadership and career stage as critical boundary conditions. Design/methodology/approach Drawing on Social Exchange Theory (SET), the Job Demands–Resources (JD-R) model, and career development theory, the framework conceptualizes AI transformation as a macro-level demand that threatens not only skills but also professional identity and perceived value. POS is positioned as a core mediating resource, while ethical leadership and career stage (mid-career) operate as key boundary conditions shaping responses to AI-driven change. Findings The model proposes that AI disruption undermines POS and, in turn, employee resilience. POS mediates this relationship, while ethical leadership strengthens its positive effects. Mid-career employees − who combine high expertise with heightened displacement anxiety − are identified as uniquely vulnerable compared with early- and late-career cohorts. Research limitations/implications Future research should empirically test the framework through longitudinal and qualitative studies across industries and cultural contexts to examine resilience trajectories during AI adoption and the buffering role of leadership and organizational practices. Practical implications The framework offers actionable guidance for leaders, organizations, and policymakers, emphasizing career-stage-sensitive reskilling, transparent AI communication, and ethical leadership practices. In service industries, these interventions help preserve mid-career talent and institutional knowledge, positioning resilience as a strategic capability rather than a peripheral HR concern. Originality/value The study contributes by reconceptualizing resilience as socially co-produced, extending the JD-R model to treat AI as a compound demand, positioning career stage as a boundary condition in social exchange processes, and clarifying how ethical leadership enhances the credibility and impact of organizational support. It frames resilience not only as an HR issue but as a strategic capability essential for sustaining competitive advantage under AI-driven transformation.

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Publication Details

Journal
Strategy and Leadership
Published
2026-02-22
DOI
https://doi.org/10.1108/sl-05-2025-0123
Primary Topic
Job Satisfaction and Organizational Behavior
Type
article
Field-Weighted Citation Impact
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article

Employee resilience under AI disruption: the mediating role of perceived organizational support & moderating effects of ethical leadership and career stage

Hiba Mounib El-Hishi
Strategy and Leadership
Job Satisfaction and Organizational Behavior
article

Employee resilience under AI disruption: the mediating role of perceived organizational support & moderating effects of ethical leadership and career stage

Hiba Mounib El-Hishi
article en

Abstract

Purpose This paper examines how artificial intelligence (AI) disruption influences employee resilience, with particular attention to the heightened vulnerability of mid-career employees. It develops a five-proposition conceptual framework that positions perceived organizational support (POS) as the central mediating mechanism and ethical leadership and career stage as critical boundary conditions. Design/methodology/approach Drawing on Social Exchange Theory (SET), the Job Demands–Resources (JD-R) model, and career development theory, the framework conceptualizes AI transformation as a macro-level demand that threatens not only skills but also professional identity and perceived value. POS is positioned as a core mediating resource, while ethical leadership and career stage (mid-career) operate as key boundary conditions shaping responses to AI-driven change. Findings The model proposes that AI disruption undermines POS and, in turn, employee resilience. POS mediates this relationship, while ethical leadership strengthens its positive effects. Mid-career employees − who combine high expertise with heightened displacement anxiety − are identified as uniquely vulnerable compared with early- and late-career cohorts. Research limitations/implications Future research should empirically test the framework through longitudinal and qualitative studies across industries and cultural contexts to examine resilience trajectories during AI adoption and the buffering role of leadership and organizational practices. Practical implications The framework offers actionable guidance for leaders, organizations, and policymakers, emphasizing career-stage-sensitive reskilling, transparent AI communication, and ethical leadership practices. In service industries, these interventions help preserve mid-career talent and institutional knowledge, positioning resilience as a strategic capability rather than a peripheral HR concern. Originality/value The study contributes by reconceptualizing resilience as socially co-produced, extending the JD-R model to treat AI as a compound demand, positioning career stage as a boundary condition in social exchange processes, and clarifying how ethical leadership enhances the credibility and impact of organizational support. It frames resilience not only as an HR issue but as a strategic capability essential for sustaining competitive advantage under AI-driven transformation.

Strategy and Leadership
Arab Open University (LB)
Openalex Percentile: Top 50%
Job Satisfaction and Organizational Behavior
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