Adaptive Capacity in the Age of Artificial Intelligence: A Critical Extension of Workforce Resilience Frameworks to Human Resource Management Functions

Abstract

The rapid advancement of artificial intelligence (AI) technologies presents unprecedented challenges for workforce management, particularly within human resource (HR) and people management functions that simultaneously face high AI exposure and serve as organizational architects of workforce adaptation. This article critically reviews and extends the emerging adaptive capacity framework introduced by Manning and Aguirre (2026), which measures occupation-level worker characteristics relevant for navigating job transitions following AI-induced displacement. While their framework advances understanding of differential workforce vulnerability, its occupation-level aggregation obscures critical within-function heterogeneity, particularly in HR domains where roles range from transactional administration to strategic business partnership. We extend the adaptive capacity framework by applying it specifically to HR functional areas, disaggregating people management occupations into distinct role clusters with varying exposure-capacity profiles. Drawing on strategic HRM theory, including the resource-based view and ability-motivation-opportunity frameworks, we develop a multi-level adaptive capacity model integrating individual, occupational, organizational, and institutional factors. Our analysis reveals that HR functions exhibit pronounced bifurcation: transactional and administrative HR roles demonstrate high AI exposure coupled with low adaptive capacity, while strategic HR business partners and organizational development specialists show moderate exposure with substantially higher adaptive capacity. Using paradox theory, we examine how HR practitioners must navigate the tension between facilitating organizational AI adaptation and experiencing their own occupational transformation. We also address equity implications, examining how differential adaptive capacity may interact with existing workforce inequities. The article offers both theoretical refinement and practical guidance for HR leaders, policymakers, and management scholars concerned with workforce resilience in an era of accelerating technological change.