Assumptions and limits
This model is deliberately narrow. It values time and direct cost only. It does not price quality improvement, customer satisfaction, risk reduction or revenue lift, because those need evidence from your own operation.
Adoption is the most common source of error. A system that works in a pilot rarely hits its full share on day one. For planning, assume a ramp and test the conservative case.
The model also ignores integration difficulty. Two systems with the same name can differ enormously in effort. List each integration and its owner before you commit budget.
Finally, the figures are not a quote. They are a planning tool. Use them to frame a conversation, then get a scoped proposal based on your actual systems and workflows.
Questions about Company Brain Readiness Score
What is a company brain?
A company brain is a connected knowledge layer that gives AI approved sources, permissions and context for a specific business.
It is not a search engine. It decides which document governs which task, and it applies the same rules to every query, which is what makes AI answers usable inside a business.
Why weight sources highest?
Without approved sources, no knowledge system can produce reliable answers.
Sources are the raw material. If records are scattered, duplicated or contradictory, the system will reflect that mess, no matter how good the model is.
What does a medium band mean?
A medium band means the foundation exists but one or two constraints will limit the first deployment.
Do not treat it as a failure. Identify the blocking gap, fix that one area, then rerun the score. Most businesses can move a band with focused work on a single input.
Can I have a high score and still fail?
Yes. Readiness is necessary but not enough. Adoption, ownership and maintenance still decide success.
A high score means the conditions are right. It does not mean the project will run itself. Name an owner and an acceptance test before you build.
How often should I rescore?
Rescore when you change systems, add a major source type or prepare a new AI use case.
A quarterly cadence is sensible for a business actively deploying AI. For a first project, score once at the start and again after the source and permission work is done.