INTELLIGENT COST GOVERNANCE IN DIGITAL SUPPLY CHAINS: INTEGRATING ARTIFICIAL INTELLIGENCE, LOGISTICS OPTIMIZATION, AND MANAGEMENT ACCOUNTING

The increasing complexity of global supply chains necessitates integrated approaches to logistics optimization, financial accountability, and data-driven decision-making. This study proposes an intelligent cost governance framework integrating artificial intelligence (AI), logistics optimization, and management accounting to examine operational performance and its implications for cost management. A quantitative, descriptive-comparative approach is adopted using publicly accessible secondary data, primarily from the World Bank's Logistics Performance Index (LPI) 2023, covering 139 economies. Ten comparative analyses are designed to examine logistics performance across countries, including customs efficiency, infrastructure, international shipments, logistics competence, tracking and tracing, and timeliness. The analysis highlights international differences in logistics capabilities, with Singapore recording an overall LPI score of 4.3 compared with 4.2 for Finland. The proposed framework connects operational indicators with predictive analytics, activity-based costing, and accounting-based performance measurement to identify opportunities for improved cost transparency and resource allocation. The study distinguishes observed logistics performance from unverified financial outcomes, recognizing that country-level data cannot independently establish AI-driven cost savings or causal effects. The research contributes an interdisciplinary framework for linking global logistics benchmarking with intelligent financial decision-making and identifies the additional organizational data necessary to evaluate cost efficiency and financial performance. The findings offer implications for logistics managers, management accountants, and policymakers seeking to strengthen data-driven governance in digital supply chains.