A Framework for AI Adoption and Strategic Decision Efficiency in Global Strategy Teams

Abstract

This paper offers an overall model of artificial intelligence implementation in global strategy teams and analyzes its effect on the efficiency of strategic decision-making in the Nigerian and West African organizational settings. In the more challenging market environments that multinational companies are operating in, particularly in emerging economies, the need to have superior decision-making capacity has never been more eminent. It uses the Technology Organization Environment framework and the Dynamic Capabilities Theory to base its researches on elements that affect the use of AI and the consequential impacts it may have on the quality, speed, and strategic performance of decisions. Using a mixed-methodology, we have surveyed 250 strategy professionals working in multinational companies and conducted an in-depth analysis of five cases of organizations of different AI maturity levels active in Nigeria. Findings indicate that organizational preparations, management dedication, and the quality of data infrastructure are significant predictors of AI adoption achievement, whereas cultural flexibility and the market environment moderate the connection amid AI adoption and decision efficiency. Structural equation modeling proved five out of six hypothesized relationships, where the organization culture is a decisive boundary condition. The qualitative data sheds light on the need to address the African markets uniquely in terms of implementation difficulties such as infrastructure limitations, talent shortage, and the necessity of contextual AI solutions. The suggested framework provides a practical insight into strategy teams in the developing economies who want to take advantage of AI technologies without losing strategic agility and cultural relevance, which adds to the literature on technology adoption and new market research