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Get Your AI Readiness Score

Answer 15 questions to see where your organization may be stuck across the four systems required to turn AI activity into business impact.

Takes about 5–7 minutes. No technical prep required.

Rating scale

Select the number that best reflects your organization today.

1 Not in place · 3 Defined · 5 Embedded

Human Operating System

Defines the roles, skills, incentives, and routines that turn employees into AI orchestrators, not passive users.

Employees understand how AI will change their work, roles, or required skills.

Not in placeEmbedded

Managers have the routines and support needed to help teams adopt AI in day-to-day work.

Not in placeEmbedded

Incentives and performance expectations encourage employees to improve work with AI, not avoid it.

Not in placeEmbedded

Use-Case Factory

Creates the execution engine that moves AI ideas from concept to pilot to production.

We have a consistent process for capturing and prioritizing AI use cases.

Not in placeEmbedded

AI pilots are evaluated against clear business cases, owners, and success metrics before they scale.

Not in placeEmbedded

There is a defined path for moving AI use cases from idea to pilot, production, and value tracking.

Not in placeEmbedded

Governance & Value Spine

Covers decision rights, guardrails, and value tracking so teams can experiment safely and prove what AI returns.

Teams understand what AI use is allowed, restricted, or requires review.

Not in placeEmbedded

Decision rights are clear enough that AI work can move forward without unnecessary bottlenecks.

Not in placeEmbedded

Legal, security, data, and business stakeholders have a clear role in reviewing higher-risk AI use cases.

Not in placeEmbedded

We track AI value through business outcomes, not only pilots launched, tools adopted, or hours saved.

Not in placeEmbedded

AI adoption and usage data is reviewed regularly by leadership.

Not in placeEmbedded

Lessons from AI pilots are used to refine priorities, governance, workflows, and future investment.

Not in placeEmbedded

Data & Access Layer

Covers the tools, data availability, and permissions that determine whether people can actually do the work.

Teams can access the data and tools they need to test AI use cases safely.

Not in placeEmbedded

Data quality, permissions, and security constraints are visible early enough to shape AI priorities.

Not in placeEmbedded

Employees know which approved AI tools, data sources, and access paths they should use.

Not in placeEmbedded

Answer all 15 questions to generate your score.