Author(s) :

ANGER, KELVIN SHIMASAAN.

Volume/Issue :

Abstract :

The accelerating integration of Artificial Intelligence (AI) into business ecosystems has transformed traditional approaches to strategic decision-making, reshaping how organizations perceive, process, and act upon complex information. This study investigates the impact of Artificial Intelligence on strategic decision-making in business management within the Nigerian context, emphasizing how AI-driven systems influence managerial efficiency, accuracy, and responsiveness. Grounded in the Technology Acceptance Model (TAM) and Dynamic Capabilities Theory, the research adopts a mixed-methods approach combining quantitative surveys and qualitative interviews to generate empirical insights from 300 managers across banking, telecommunications, manufacturing, and logistics sectors. The findings reveal that AI technologies particularly machine learning, predictive analytics, and natural language processing significantly enhance decision quality by improving forecasting accuracy, optimizing resource allocation, and reducing cognitive biases in managerial judgments. Results further indicate that firms with adaptive learning cultures and strong digital infrastructures demonstrate higher levels of AI assimilation and strategic agility. However, infrastructural deficits, limited digital literacy, and ethical concerns such as algorithmic bias and data insecurity continue to constrain AI’s full potential in Nigeria’s corporate landscape. The study concludes that AI functions not merely as an operational enabler but as a transformative strategic capability that redefines organizational competitiveness, leadership reasoning, and long-term sustainability. It recommends targeted investments in digital infrastructure, capacity development, and ethical AI governance to strengthen Nigeria’s readiness for data-driven strategic transformation. The findings contribute to the growing scholarship on digital innovation and strategic management in emerging economies, offering theoretical and practical implications for policymakers, scholars, and business leaders seeking to align technological adoption with sustainable competitive advantage.

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