Adoption of Generative AI in Business Decision-Making: Opportunities, Risks, and Strategic Readiness in Emerging Markets

The rapid evolution of Generative AI has opened up numerous possibilities to enhance organizational decision-making through improved operational efficiency, innovation, and data analysis accuracy. However, companies in developing countries face challenges such as underdeveloped digital infrastructure, labor shortages, data security risks, and regulatory uncertainty. These factors create a gap between theoretical benefits and practical implementation. This study explores opportunities, key risks, and organizational readiness for Generative AI adoption in business decision-making within developing countries. Using a mixed-method sequential design, phase I involved a quantitative survey of 120 companies across five nations, while phase II included interviews with 15 key informants. Data were analyzed using Structural Equation Modeling and NVivo, with interactive visualization aiding in framework development. Findings indicate that Generative AI could improve decision-making efficiency by 89% and reduce operational costs by 15%. Top risks include data security (score: 4.41) and regulatory ambiguity (score: 4.27). Organizational readiness was high in managerial support (score: 4.01) but low in internal regulation (score: 3.67). The proposed Strategic Generative AI Adoption Framework integrates innovation diffusion, risk management, and readiness, offering practical insights for adaptive AI adoption in developing countries.