Most organisations know AI is critical. Few know what that actually changes in how they operate. Leaders are being told to "use AI”, teams are experimenting with tools, pilots are everywhere, but there’s no shared framework to measure readiness or decide what to do next. The risk isn’t inaction; it’s random action.

AI readiness is about structure. It is a way of understanding whether your organisation can use AI deliberately, safely, and at scale. Without that structure, efforts fragment - content teams do one thing, IT does another, marketing another - and nothing compounds into real outcomes.

To fix that, you need a model that benchmarks your capabilities and gives you a clear path from where you are to where you need to be. That’s the purpose of the Codehouse AI readiness assessment: a practical, business-focused diagnostic that cuts through hype and exposes where progress is happening, and where gaps are slowing you down.

Why you need an AI readiness assessment

• Most organisations sit in "AI awareness" mode, not “AI operations” mode.

• Leaders say AI is important, but cannot articulate what should change in workflow, governance, or measurement.

• Teams run isolated pilots with no shared standards, no alignment, and no clear returns.

• Content and metadata are rarely structured enough to support AI accuracy, governance, safety, or scalability.

• Organisations have no baseline against which to measure maturity, investment, or progress.

A structured AI assessment solves this by giving you:

• A shared language and maturity scale.

• A baseline maturity score across your organisation.

• A way to prioritise investment based on what will move maturity forward.

• A roadmap grounded in capability development, not guesswork.

How the assessment works

At the recent Sitecore Symposium, I ran a shortened 10-question version of the assessment. Each table picked one volunteer, discussed each question, and scored their organisation from 0 to 3. The goal was clarity: where do you sit today, and what does that mean?

The full version expands this to 30 diagnostic questions across five core dimensions. It is designed for leadership teams, digital teams, content teams, and operational teams to complete together.

Scoring is simple:

0 = Not in place

1 = Early or inconsistent

2 = Defined and operational

3 = Integrated and optimised

The goal isn’t the number. It’s the pattern. You’re looking for uneven maturity, capability gaps, and friction points between teams. That’s where improvement delivers the highest return.

The five dimensions of AI maturity

Strategy and vision

• Is AI embedded in your digital and organisational roadmap?

• Is there clarity on what AI changes in workflows, governance, customer journeys, and measurement?

Governance and policy

• Are roles, rules, and accountability defined?

• Are ethics, safety, compliance, and security frameworks in place?

Content and metadata

• Is your content structured, tagged, accurate, and consistent?

• Is metadata designed to support generative AI, search, personalisation, governance, and localisation at scale?

Measurement

• Are you tracking outcomes AI can influence?

• Do you know the ROI of experiments or production use cases?

Enablement

• Are your people trained, confident, and equipped to use AI in their day-to-day work?

• Is there a culture of responsible experimentation?

Maturity levels

Foundational

• AI awareness without structure.

• Experiments happening in isolation.

• Policies unclear or nonexistent.

• Content and metadata not AI-ready.

Operational

• Defined AI policies and clearer ownership.

• Early pilots connected to business outcomes.

• Consistent metadata practices emerging.

• Training and enablement starting to take shape.

Intelligent

• AI integrated systematically into workflows.

• Content, metadata, governance, and measurement linked.

• Clear metrics and continuous optimisation.

• AI treated as an operational capability, not a one-off experiment.

How to use the 30-question assessment

Step 1: Run it with your leadership and operational teams separately. Compare maturity gaps.

Step 2: Identify the lowest-scoring dimension. That’s your highest-impact next investment.

Step 3: Build a short, targeted 90-day plan per dimension to lift maturity from one level to the next.

Step 4: Re-assess every six months to track progress, justify investment, and maintain alignment.

The value is not the assessment itself. It’s the alignment it forces. Most organisations move quickly once they have a shared view of reality.

Download the full 30-question AI readiness assessment

The full diagnostic is available for download. Use it with your team to benchmark where you are today and identify where to invest next to build AI capability that actually compounds.

If you want help running a facilitated session, interpreting the results, or turning your maturity score into a roadmap, we can support you.