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Jeremy Taylor

Writing about the gap that matters most in enterprise AI right now — the one between experimentation and operational value — as a six-pillar operating model.

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The framework

The Enterprise AI Operating Model

Every organization differs, but these six pillars are universal requirements for moving from experimentation to the value phase.

  1. Strategy & Value Realization Delivering value against a defined hypothesis.
  2. AI FinOps Understanding costs and connecting them to their value.
  3. Technology & Operations Defining the platforms and architecture for deployment.
  4. Data Management & Intelligence Establishing ownership, stewardship, and a context layer for AI.
  5. People & Enablement Driving democratization, training, and communications.
  6. Risk, Ethics & Policy Navigating threat vectors, privacy, and least privilege.

The series

Essays

A detailed essay on each pillar is in preparation — beginning with Strategy & Value Realization, AI FinOps, and Technology & Operations.

Want to know when they publish? Reach out on LinkedIn and I'll let you know as each one goes up.

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Continue the conversation

I'm always up for a discussion about enterprise AI operating models — what's working, what isn't, and where the model above breaks down against a real environment.

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