�𝐫𝐨𝐦 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐀𝐮𝐠𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧: How AI Adoption Influences Managerial Decision-Making and Organizational Performance

Artificial intelligence (AI) is increasingly embedded in managerial work, yet its organisational value cannot be explained by adoption alone. AI can automate bounded tasks, augment managerial judgement, or combine both roles across different decision stages. This conceptual paper develops an integrative framework explaining how AI adoption influences managerial decision-making and organisational performance through human–AI collaboration and decision implementation. Drawing on the automation–augmentation paradox, sociotechnical systems thinking, decision-making theory, and dynamic capabilities, the paper argues that AI creates value when analytical capabilities complement managerial contextual knowledge and are embedded in accountable routines. The framework proposes that AI adoption influences decision quality through information processing, option generation, and decision support; decision quality contributes to performance when decisions are implemented effectively. Human–AI collaboration is pos