AI Readiness Assessment: your AI roadmap, ranked by P&L impact and risk

This is not a questionnaire. It is the plan you would pay a consultancy for, written so your team can act on it with us or without us.

Owners and operations leaders with a business objective and a reason to act: grow revenue, protect margin, free up leadership time, keep expertise in the company. You do not need to arrive with an AI use case. You need to know what you want to change.

The pattern is the same everywhere we go: trucking and logistics, contractors and field service, industrial shops, hospitality groups, and any business where the work happens in a TMS, an FSM, an ERP, and a dozen inboxes and portals. Systems that do not talk to each other. A person standing in the gap, re-keying and checking. Knowledge that lives in three heads. An owner who cannot get a straight number without someone building a spreadsheet. If that is you, the question is not "which AI tool" but "which objective, which job, first, and what is it worth."

It is not a maturity score. Plenty of vendors will grade your "AI readiness" on a five-point scale and send a PDF. A score does not tell you which job to hand to an agent first or what it is worth.

It is not a technology recommendation. We do not arrive with a platform to sell. Most of what we recommend runs inside software you already pay for, and some of it is a plain integration or a reliable rule, not AI.

It is not a discovery call dressed up as a deliverable. Two days on site, with your dispatch, billing, and office staff, is work. The output is a document your team will argue with, which is the point.

And it is not a commitment. You keep the roadmap and the governance notes whether or not you build with us, and they are written so anyone competent could act on them.

Every candidate initiative is scored on what it changes in one of five places: revenue, margin, labor hours, cash cycle, and error cost. Capacity, continuity, and risk count too, with the economics behind them stated rather than assumed. If we cannot name the line and the assumption, it does not make the roadmap.

That is the difference between this and an AI strategy deck. A deck tells you AI is important. The roadmap tells you that the AP capture agent saves roughly this many hours a month, touches these two systems, and carries this much risk if it codes an invoice wrong, so it ranks third, behind the two things that pay back faster with less exposure.

Risk is scored too: data sensitivity, what happens if the agent is wrong, how many systems it touches, and how much a person needs to stay in the loop. High value and low risk goes first. High value and high risk gets a governance plan before it gets built. Low value goes on the list with a note, because the list is also a record of what you decided not to do and why, which is useful the next time a vendor pitches it.

Day one: objectives, people, process, technology. We start with the owner and the managers on what the business needs to achieve and which numbers define progress. Then we walk your operation with the people who do the work, not only the people who manage it. Dispatch, billing, intake, scheduling, reporting. We see the four browser tabs, the re-keying, the spreadsheet that runs the company. We inventory your systems and what each one can and cannot exchange.

Day two: scoring workshop. With the owner and the managers in the room, we put every candidate on the board and score it on value and risk against your objectives. We argue about the numbers. We settle on a ranked list and on the one thing to build first.

What you leave with. The ranked roadmap, with the P&L line, the assumptions, and the systems for each item. A business case for the recommended first initiative, with the alternatives we rejected and why. Governance notes: where a person must stay in the loop, what data needs care, and what the documentation should say. A systems inventory: what each one can exchange, what has an API, what does not. A fixed-scope proposal for the first build, with acceptance tests written down. All of it yours, whether or not we do anything else together.

Before we arrive. We ask for read access to your main systems where practical, a list of the people we should talk to, and the three things that frustrate the owner most. We do not need clean data or a data team. We need a morning with the people who do the work.

The assessment ends with a fixed-scope proposal for the first initiative: one eligible workflow, touching up to three systems, with access, test data, and an owner on your side in place before the clock starts. The build is quoted separately, and the assessment fee is credited once against it.

Every first build has acceptance tests in writing before we start. If it misses them, the build fee is waived. You keep the code, the data, and the accounts either way. Most clients ask for an AI agent for a back-office job first: AP or AR, dispatch status, intake, or the weekly owner report. Twelve back-office agents we assess for →

If you already know exactly what you want built and it is well defined, you can skip the assessment and go straight to a scoped build. Most of the time the assessment changes what gets built first, which is why we credit it rather than waive it.

The AI Readiness Assessment starts at $10,000. That amount is credited once against your first build workstream, within twelve months. If your first engagement is quoted at $40,000 including the assessment, you pay $10,000 for the assessment and $30,000 for the build. It is not $50,000, and the credit does not apply again to a later build. Larger operations with more sites or systems are quoted before we book.

Prices verified September 2026. Full pricing, credit terms, and the guarantee →

Pick a 30-minute slot below. We confirm fit on that call, then schedule the two days. Prefer to write first? The form is under the calendar.

Prefer to talk first? Call 346.560.5759. A founder answers or calls back within one business day.