ASSESSING ORGANIZATIONAL AI READINESS IN CRITICAL INFRASTRUCTURE: AN INTEGRATED MATURITY FRAMEWORK FOR HEALTHCARE SYSTEMS AND SUPPLY CHAIN MANAGEMENT

Abstract

Critical infrastructure sectors face unprecedented challenges requiring artificial intelligence (AI) integration to enhance operational resilience and national security. However, AI adoption remains limited due to inadequate organizational readiness assessment frameworks. This research develops and validates a comprehensive AI readiness maturity model adapted from the Capability Maturity Model Integration (CMMI) framework for healthcare systems and supply chain management. Drawing on Technology-Organization-Environment (TOE) theory, Resource-Based View (RBV), and Dynamic Capabilities Theory, we propose an integrated assessment framework encompassing six dimensions: Technical Infrastructure, Data Capabilities, Organizational Capabilities, Strategic Readiness, Governance and Ethics, and Ecosystem Integration. Through multi-method validation involving survey data from 312 organizations, 45 semi-structured interviews, and four longitudinal case studies, we demonstrate strong psychometric properties and significant positive relationships between AI readiness maturity and infrastructure resilience outcomes. Results reveal that only 23% of healthcare organizations and 18% of supply chain organizations achieve optimized maturity levels, with significant gaps in data capabilities and governance structures. Our findings provide actionable frameworks for practitioners, inform policy development for critical infrastructure protection, and establish theoretical foundations for future research on AI-enabled infrastructure resilience.