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Operating Model

The operating model describes how a company turns AI from scattered pilots into a managed adoption system: from idea and AI product selection to implementation, usage, and confirmed impact.

The section answers five base questions.

Principles​

What rules underpin AI adoption and help avoid pilot chaos, duplicated solutions, and tech hype.

Roles​

Who owns what in the AI function: strategy, infrastructure, products, initiatives, training, adoption, and result confirmation.

Entities​

What the operating model actually manages: AI ideas, initiatives, AI products, business funnel, delivery tracks, stage gates, artifacts, risks, and impact.

Processes​

How AI initiatives and AI products move from incoming demand to adoption, operations, and scaling.

Rituals​

Where regular decisions are made: what to take on, what to stop, which products to grow, where blockers are, and which impact is confirmed.

Core idea of this section​

The AI function should be neither an experiment lab nor a request dispatcher, but a management layer that helps the company adopt AI safely, repeatably, and measurably.