ARTIFICIAL INTELLIGENCE ADOPTION AS A DRIVER OF ORGANIZATIONAL AGILITY IN MANAGEMENT

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology that is reshaping organizational processes, strategic decision-making, and competitive advantage across industries. In today's dynamic and highly competitive business environment, organizations must continuously enhance their agility to respond effectively to technological disruptions, changing customer expectations, and market uncertainties. This study examines the relationship between Artificial Intelligence Adoption (AIA) and Organizational Agility (OA) while assessing the influence of Organizational Context (OC) from a management perspective. The research aims to investigate how AI adoption contributes to organizational agility and whether organizational context significantly influences this relationship. The study adopts a quantitative research approach using a structured questionnaire administered to managerial and professional employees across various industries. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate both the measurement and structural models. The measurement model was assessed through Cronbach's Alpha, rho_A, Composite Reliability (CR), and Average Variance Extracted (AVE), while the structural model was examined using bootstrapping techniques to test the proposed hypotheses. The findings demonstrate that all constructs exhibit excellent reliability and convergent validity, with Cronbach's Alpha values exceeding 0.94, Composite Reliability values above 0.95, and AVE values greater than 0.70. Structural model analysis reveals that Artificial Intelligence Adoption has a significant positive effect on Organizational Agility (β = 0.708, p < 0.001) and Organizational Context (β = 0.962, p < 0.001). Furthermore, Organizational Context significantly influences Organizational Agility (β = −0.378, p = 0.013), indicating that certain contextual organizational characteristics may constrain agility despite increased AI adoption. These findings suggest that while AI serves as a strategic capability that enhances organizational responsiveness and innovation, its effectiveness depends on the presence of supportive organizational structures, leadership, and an adaptive culture. The study contributes to the literature by integrating perspectives from the Technology–Organization–Environment (TOE) Framework, Resource-Based View (RBV), and Dynamic Capabilities Theory to explain the role of AI in improving organizational agility. From a practical perspective, the findings emphasize that organizations should complement AI investments with flexible organizational structures, transformational leadership, employee capability development, and innovation-oriented cultures to maximize the benefits of digital transformation. The study concludes that Artificial Intelligence is not merely a technological innovation but a strategic organizational capability that enables firms to achieve sustainable competitiveness and long-term organizational agility in an increasingly digital business environment.