Abstract
Artificial
Intelligence (AI) is increasingly central to business and public-sector
organizations, offering transformative potential in productivity,
decision-making, service delivery, and innovation. Despite this promise, many
AI initiatives fail due to strategic misalignment, fragmented governance, and
limited integration of technical and organizational factors. This paper
introduces AI Management as a novel subfield of management science, presenting
a structured framework for the effective adoption, operationalization, and
oversight of AI initiatives. The framework integrates ten core functions—AI
Leadership, AI Strategy, AI Transformation, AI
Operationalization (ModelOps), AI Security, AI Performance & Value
Management, Data Governance, AI Governance, AI Culture, and AI Risk
Management—across vertical, horizontal, and pillar dimensions. By embedding
ethics, regulatory compliance, strategic alignment, and value creation into
organizational processes, AI Management provides a systematic approach for
scaling AI responsibly, bridging its transformative potential with practical
outcomes, and enabling sustainable organizational and societal impact.
