Government Organizational Readiness in the Artificial Intelligence Era: A Dynamic Capabilities Analysis

Abstract

The rapid advancement of artificial intelligence (AI) has fundamentally transformed public administration by creating new opportunities to improve public service delivery, evidence-based policymaking, administrative efficiency, and governance innovation. However, despite increasing governmental investments in AI technologies, many public organizations continue to encounter organizational barriers that hinder successful AI adoption. Existing studies predominantly conceptualize AI readiness from technological, organizational, or institutional perspectives, while relatively limited attention has been devoted to understanding organizational readiness as a dynamic capability that enables governments to continuously adapt to technological change. This study aims to develop a comprehensive conceptual framework for government organizational readiness for artificial intelligence adoption through the lens of Dynamic Capabilities Theory. A conceptual literature review approach was employed by critically synthesizing peer-reviewed studies on artificial intelligence, digital government transformation, organizational readiness, and Dynamic Capabilities Theory. The review integrates contemporary theoretical and empirical literature to identify the key dimensions of AI readiness and explain their relationships within a unified conceptual model. The findings indicate that government organizational readiness extends beyond technological preparedness and is shaped by the interaction of six interrelated dimensions: strategic leadership and vision, digital infrastructure and technological capability, human capital and digital competencies, organizational culture and change readiness, governance and ethical preparedness, and interorganizational collaboration. These dimensions collectively strengthen governments' sensing, seizing, and reconfiguring capabilities, enabling continuous organizational adaptation during AI-driven digital transformation. Based on this synthesis, the study proposes an integrated analytical framework that conceptualizes AI readiness as a dynamic organizational capability rather than a static pre-adoption condition. The proposed framework contributes to the literature by extending existing AI readiness models through the integration of Dynamic Capabilities Theory and offers practical guidance for policymakers and public managers in designing adaptive, ethical, and sustainable AI implementation strategies. Future research is encouraged to empirically validate the proposed framework across different governmental contexts to enhance its generalizability and practical applicability.