Jeremy Taylor

Publications

Library

One model, published in pieces. The operating model is the spine. What follows adds to it: more depth where depth is needed, and angles that cut across several pillars at once.

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  Published

  The Enterprise AI Operating Model

  Ask a leadership team what they're doing with AI, and you'll get a list. Ask which items on that list are paying for themselves, and the room gets quiet. Six pillars for turning activity into value someone can name, attribute, and defend.

  Version 1.1 Revised October 1, 2026 About 20 minutes PDF

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  Published

  The Federated Data Governance Program

  A companion to the Data Management pillar of the operating model, delivering minimal governance for integrating trustworthy AI context: federated ownership, a five-layer role model, and a Bronze/Silver/Gold certification rubric.

  Version 1.1 Revised October 1, 2026 About 22 minutes PDF

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 Which use cases deserve our scarce resources?
2. AI FinOps What is this costing, and against what value?
3. Data Management & Intelligence Can the agent be trusted with our context?
4. Technology & Operations What do we build, what do we buy, and how do we know it still works?
5. People & Enablement Will anyone actually use what we deploy?
6. Risk, Ethics & Policy What are the boundaries, and who is accountable?

About

Who is writing this

I lead global data and AI organizations with twenty years in technology. I've spent the past eleven years building and transforming cloud data platforms. Most recently, I've focused on adding an AI platform layer and agents in production.

I completed the Carnegie Mellon University Chief Data and AI Officer executive certificate in 2026. This model came out of that work.

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