This is a self-assessment. You answer fifteen questions about how technology is actually run in your organization. The page returns a maturity level across ten areas, the gaps worth fixing first, and what closing them with a full-time hire would cost using published federal wage data.
Your answers stay in your browser. Nothing is scored on our servers and nothing is sent to us unless you ask for the written summary at the end. Close the tab and it is gone.
Every gap above is work somebody has to own. If that somebody is a full-time technology executive, this is the published cost of the seat, before recruiting, equity or severance. The salary figure is the national median for the role. The benefit load is a share of total compensation, not a markup on salary, so the total is base divided by one minus the share.
Annual, whatever figure you are working with, from any provider. We do not publish rates here because scope, not a rate card, sets them. To change the salary benchmark or the benefit load, use the full cost model.
We will send your results as a plain document you can forward to your board, your auditor, or whoever is going to have to fund the fix. No obligation, and no sales sequence.
We will send the written summary shortly. If you want these gaps walked through against your actual environment, the AI-Readiness Diagnostic is the next step.
It takes fifteen answers about how technology is run day to day and reports them back as a maturity level across ten areas, on a scale from zero to three.
This is a self-assessment. It reports what you told it, and nothing more. It is not an audit, an assessment, a certification or legal advice.
The AI Policy Check deliberately has no score. It reads a document, and a document cannot tell you whether a control actually operates, so a number there would be false precision.
This is different. You are rating your own operation, so the number is a tally of your own answers rather than a judgment about evidence. It is only ever as accurate as the answers you gave.
The salary is the national median for Computer and Information Systems Managers, the federal occupation code covering technology leadership. Your market may sit well above or below it.
Benefits are quoted by BLS as a share of total compensation, so the total is base divided by one minus that share. Treating it as a markup on salary understates the number. Recruiting fees, equity, bonus and the cost of a bad hire are excluded.
The AI Policy Check reads your written AI policy against the framework your auditor will use, in your browser, in about a minute. It quotes the sentence behind every finding.