Leveraging AI for geo-economic decisions: navigating the nexus between business process management, knowledge management and business intelligence practices

Purpose – The purpose of this study is to explore how artificial intelligence (AI), integrated with business process management (BPM), knowledge management (KM) and business intelligence (BI), can optimize decision-making in geo-economic contexts, utilizing the resource-based view (RBV) theory. Design/methodology/approach – Data were gathered from over 280 professionals representing listed information technology companies in northern India using a structured questionnaire. Convenience sampling was employed for data collection. The measurement and structural models were tested using partial least squares structural equation modeling (PLS-SEM). Findings – AI adoption significantly improves BI, BPM and KM practices though it has no direct effect on geo-economic decision-making (GEDM). BPM, however, strongly drives both GEDM and KM, positioning it as a key strategic enabler. Mediation analysis shows that BI and BPM partially transmit AI's influence on organizational decision-making. Originality/value – The research provides a new perspective on how AI can be combined with BPM, KM and BI in GEDM. This approach provides insight into how a network of interconnected resources leverages organizational capabilities – a contribution with new insight for leveraging performance in complex, dynamic global environments, particularly through the application of RBV theory to create value.