AI-Driven Transformation: The Role of Artificial Intelligence in Strategic Business Decision-Making

This thesis examines the transformative impact of Artificial Intelligence (AI) on strategic business decision-making, offering an in-depth analysis of how AI is reshaping the corporate environment. The primary aim of the study is to explore the emergence and progression of AI within business strategies, particularly its role in challenging traditional decision-making models and enhancing organizational adaptability. Through a comprehensive literature review of both academic and industry literature, the research provides a detailed understanding of AI’s various effects on business. To address these research questions, a mixed-methods approach was adopted, combining quantitative data from a survey of 250 respondents with qualitative insights drawn from four case studies: Satispay, Aiko, Accenture, and Amazon. Additionally, interviews with AI professionals from Accenture and Aiko provided in-depth perspectives on the practical implications of AI adoption. The findings indicate that AI is significantly enhancing data-driven decision-making, improving operational efficiency, and enabling predictive analytics in strategic processes. Larger firms such as Amazon and Accenture are leveraging AI extensively across multiple functions, while smaller firms like Satispay and Aiko are implementing AI in targeted applications, such as fraud detection and autonomous satellite operations. However, the study also highlights barriers to AI adoption, including a lack of skilled personnel, high implementation costs, and ethical concerns around data privacy and algorithmic bias. These challenges are particularly difficult for smaller firms and highly regulated industries. At the same time, AI offers substantial opportunities for improving decision-making accuracy, reducing operational costs, and fostering innovation in customer engagement.