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Strategic Adoption of Artificial Intelligence in Business: Measuring Efficiency, Financial Performance, and Cybersecurity Governance

Artificial intelligence has shifted from being a secondary technology to becoming a decisive factor in corporate survival. It is no longer an optional enhancement but a structural necessity for modern business. AI systems are not simply automating tasks; they are reshaping how organizations operate, how they compete, and how they safeguard sensitive information. This transformation is especially visible in Asia, where governments and enterprises are driving adoption as part of national development strategies and corporate restructuring. Despite this rapid progress, there is still a major gap in understanding how AI’s impact should be measured and governed. Much of the existing research focuses on productivity claims or financial outcomes in isolation, while overlooking the deeper connections between efficiency, profitability, and cybersecurity governance. This dissertation addresses that gap by examining how AI is strategically adopted in Asia, with a focus on large enterprises that face both opportunities and constraints.