From Trials to Results – A Novel Capability Framework for Companies to Lead AI Deployment with Results

Interest and investments in AI have grown significantly in recent years, but tangible results and benefits for companies still remain limited. The few existing academic articles acknowledge the lack of theoretical frameworks and show that AI deployment is still in the early stages. In this study, we use empirical data collected through semi-structured interviews with chief information officers to examine AI deployment in leading international publicly listed companies. We employ Abductive analysis and the Capability View to uncover, analyze, and explain our findings. The results confirm that companies are at different stages of deployment and suggest that progress depends on a broader set of capabilities than previously reported in peer-reviewed literature. We identify and define eight critical capabilities that explain differences in strategies, approaches, and outcomes among companies. We develop and propose a strategy-based AI Deployment Capability Framework (AI-DCF) as a foundation for future research and AI deployment in companies. The AI-DCF characterizes AI deployment as a comprehensive, multi-year, multi-competency process and emphasizes the vital role of top management in guiding and leading this effort. This framework and the findings help companies develop and manage their capabilities holistically, focusing on key areas and overcoming obstacles to harness data and AI to increase productivity and competitive advantage. To our knowledge, this is the first study to identify, analyze, and explain, at the management level, the essential capabilities needed to achieve tangible results and benefits from AI deployment.