OPEN SOURCE AI OPERATING MODEL

AI stalls in the in-between

AI initiatives don't fail because models break — they fail where ownership, governance, and value fall apart between idea and production. We're providing a proven AI Operating Model completely free and open source so you can learn where you benchmark in the model.

THE OPEN MODEL

What actually works

We codified what consistently worked: clear ownership, embedded governance, continuous value measurement. Then we made it public.

We didn't theorize this into existence.

We built it from patterns that consistently deliver results.

Foundation

Strategy alignment

Governance framework

Team enablement

Lifecycle

Plan → Build → Run

Clear stage gates

Defined handoffs

Artifacts

Shared templates

Role definitions

Process documentation

Value

Continuous measurement

Business alignment

Impact tracking

FREE RESOURCES

AI Operating Model Workbooks

Concrete templates, checklists, and frameworks that plug directly into your current workflow.

Start building your AI operating model today.

AI OpModel Foundations

Turn AI chaos into repeatable value

Define the people, processes, and platform patterns that eliminate bottlenecks, accelerate deployment, and deliver measurable business value.

Clear roles & responsibilities

Defined handoffs

Built-in compliance controls

Scope & Structure

Define clear boundaries

Without clear boundaries, AI operating models become ambiguous and ineffective. Define exactly where your model applies—and where it doesn't.

Defined scope

Clear end goals

Focused constraints

AI Life Cycle

Map your AI journey

Define how AI projects flow through your organization from idea to production deployment and ongoing maintenance with clear stage gates.

Stage definitions

Team handoffs

Definition of done

Use Cases & Value

Operationalize value delivery

Create clear, consistent frameworks that assess and deliver tangible, measurable impacts on the business from AI initiatives.

Clear prioritization

Structured business cases

Success criteria alignment

AI Governance

Integrate risk management

Establish an AI governance program that creates controls for managing each individual use of AI within your organization.

Policies & controls

Ongoing review & audit

Regulatory alignment

PROVEN INSIGHT

We've seen this
over and over

This isn't a hypothesis. It's an observed pattern across dozens of enterprise AI implementations.

AI doesn't fail because models break.

It fails where ownership, governance, and value fall apart between idea and production.

Enterprise-tested

Implemented AI operating models across Fortune 500 companies and growth-stage enterprises.

Cross-industry

Financial services, healthcare, retail, technology — the pattern persists across domains.

Maturity agnostic

Whether teams are starting or scaling AI, the breakdown occurs in the same places.