Key takeaways
Last updated
The AI Readiness Playbook interprets readiness signals and converts them into a prioritized 90-day plan covering governance, architecture, and measurement.
It is the step after assessment: it assumes you already know where you score and need to decide what to do about it.
Sequencing guidance is dependency-ordered, so data and governance groundwork precedes the use cases that depend on it.
Frequently Asked Questions
Common questions about AI Readiness Playbook
Interpretation guidance for readiness signals, a prioritization framework for the next 90 days, governance and architecture starting points, and a measurement approach that establishes baselines before any workflow changes.
It is most useful with them, since the playbook is organized around interpreting scores. Without results, start with the AI Readiness Checklist or the online assessment and return to the playbook afterward.
A dependency-ordered sequence: governance and ownership decisions first, data and integration groundwork second, and the first scoped use case third, each with defined outputs and a measurement baseline captured before changes begin.
An execution plan. It assumes strategy questions about where AI belongs are already settled and focuses on ordering the work so that the first initiatives can actually reach production.
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