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AI Operating Model

An AI Operating Model defines how an organization structures its people, processes, governance, and technology to manage AI systems effectively.

AI Operating Model

Overview

Successfully managing artificial intelligence requires more than technology.

Organizations also need a clear way of organizing people, processes, and responsibilities.

This structure is known as an AI Operating Model.

An AI Operating Model defines how an organization organizes its people, processes, governance, technology, and decision-making to develop, deploy, and manage AI systems effectively.

An operating model typically defines:

  • Organizational roles
  • Governance responsibilities
  • Decision-making processes
  • AI workflows
  • Risk management activities
  • Collaboration between business and technical teams

A helpful way to think about an operating model is an organization’s blueprint for how work gets done.

Rather than focusing on one AI project, it explains how the entire AI program operates.

A well-designed AI operating model supports AI Governance, AI Accountability, and AI Lifecycle Management.

Why It Matters

An AI operating model improves coordination, accountability, governance, and consistency across an organization’s AI initiatives.

Real-World Example

A multinational company defines an AI operating model that assigns responsibilities to business leaders, data scientists, risk managers, legal teams, and governance committees throughout every AI project.

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