Artificial Intelligence Adoption in Organizations: A Management Framework for Improving Decision-Making and Operational Performance

Abstract

This study aims to examine the emerging adoption of artificial intelligence (AI) within organizations and develop a managementoriented
perspective linking AI utilization with organizational decision-making and operational performance. The study seeks to
examine the extent to which organizations employ AI across workflow automation, decision support, strategic decision-making,
and sourcing, procurement, and supply-chain activities. It further aims to provide an empirical foundation for understanding the
organizational conditions required for broader AI integration. The analysis uses establishment-level data from the World Bank
Enterprise Survey–Follow-up on Artificial Intelligence (WBES-OS), India, 2026, covering 1,355 establishments. The findings show
that AI adoption remains limited across the examined organizational functions. Only a small proportion of establishments reported
using AI for workflow automation and decision support, while strategic decision-making and supply-chain applications also
showed relatively limited adoption. The results indicate that organizations are at different stages of AI integration and continue
to rely substantially on conventional processes. The study concludes that organizational AI adoption in India is still developing
and requires greater attention to technological readiness, organizational capabilities, employee competencies, managerial
involvement, and effective integration with existing processes. The findings provide a foundation for future empirical investigation
into whether AI adoption contributes to decision-making effectiveness and operational performance.