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AI-Enabled Airline Digital Core Modernization: A KPI-Governed Design Science Framework for Intelligent and Predictive Airline Operations
Airline digital transformation is increasingly constrained not by the absence of technology projects, but by the absence of a governed digital core that connects enterprise architecture, trusted data, redesigned workflows, artificial intelligence (AI), cyber resilience, KPI accountability, and leadership execution. Existing airline studies have examined digital transformation, retailing, predictive maintenance, AI-supported disruption management, enterprise architecture, cybersecurity, and performance measurement, yet these streams often remain domain-specific. This paper develops ADCM-360 as a Design Science Research artifact for airline digital core modernization. The framework integrates seven layers: systems integration; data governance and intelligence; process modernization; AI and predictive operations; governance, risk, compliance, and AI assurance; performance and value realization; and leadership, transformation, capability, and adoption. It is grounded in the principle of Universal Core + Adaptive Execution: all airlines require a common modernization logic, but execution must be calibrated to airline type, digital maturity, fleet complexity, regulatory context, budget, data readiness, and strategic priorities. The paper contributes a theory-informed artifact, a KPI-governed maturity trajectory, a pilot-to-production AI governance logic, and a legacy-risk-to-control mapping. Because the paper is conceptual and design-science based, it does not claim completed empirical validation. Instead, it proposes a validation pathway through expert Delphi review, case demonstration, maturity assessment, KPI testing, and longitudinal value tracking. The contribution is relevant to information technology, AI governance, intelligent transport systems, cybersecurity, enterprise architecture, and technological futures studies.
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