Agentic AI as a catalyst for enhancing risk management and organizational resilience in service sector: challenges, opportunities and theoretical directions
Abstract
As service organizations increasingly adopt agentic artificial intelligence (AI) systems, there is a pressing need to understand the relationship between agentic AI and the practices of risk management and organizational resilience areas that current frameworks do not adequately address. This study aims to explore the associations between agentic AI, enterprise risk management (ERM) and organizational resilience in the service sector. This study used integrated research design that included both expert validation through the fuzzy Delphi method along with quantitative methods of data collection on a sample of 2,183 respondents. This study estimated direct, indirect and multiple group comparisons relationships among the constructs, using structural equation modeling. The results of this study indicate that agentic AI is significantly associated with ERM and organizational resilience. Risk intelligence, AI governance and human–AI coordination are associated with these relationships, while regional differences are moderately associated with the strength of these associations. The findings of this study highlight the importance of aligning socio-technical mechanisms with autonomous technologies in relation to organizational resilience. This study provides managers with actionable insights for integrating agentic AI into ERM practices. Implementation can be associated with greater operational efficiency, customer satisfaction and risk mitigation, while emphasizing the need for governance structures and human–AI coordination to maximize benefits. Traditional ERM, resilience and socio-technical frameworks seldom consider the autonomous decision-making of agentic AI or its systemic impact on risk and resilience. This study addresses this gap by integrating agentic AI into these models and demonstrating its unique role in the evolution of risk management, resilience and workflows in the service sector.