From Automation to Augmentation: The Changing Role of AI in Management

Artificial intelligence (AI) entered the managerial domain largely as an instrument of automation, promising cost reduction through the substitution of human effort in structured, repetitive and rule-governed tasks. A decade of organisational experience has revealed that this substitution logic captures only a narrow slice of the value that intelligent systems create. Increasingly, the dominant design is augmentation, in which algorithmic and human intelligence are configured as complementary contributors to a single decision process rather than as rivals for the same task. This paper examines the intellectual and practical migration from automation to augmentation and asks what it implies for the theory and practice of management. Adopting a systematic literature review protocol, the study analyses 118 peer-reviewed articles published between 2015 and 2025 in management, information systems and organisation studies outlets, supplemented by a qualitative synthesis of 24 documented industry cases. Six thematic clusters are identified: task decomposition and division of labour, decision augmentation and judgement, managerial role reconfiguration, trust and explainability, workforce reskilling, and governance and accountability. Building on this synthesis, the paper develops the A3 Framework (Automate, Assist, Augment), a three-stage maturity model that positions organisational AI deployment along the dimensions of task structure, decision reversibility, human oversight and value logic. The findings indicate that automation and augmentation are not sequential stages of technological progress but interdependent configurations that must be managed simultaneously; that the scarce resource in AI-enabled organisations is not computational capacity but managerial judgement, contextual sense-making and accountability; and that the principal barrier to augmentation is organisational rather than technical, residing in incentive systems, trust calibration and role design. The paper contributes a conceptual vocabulary for augmentation-oriented management, offers a diagnostic instrument for practitioners, and outlines an agenda for empirical research.