Toolkit · ZIP · 7 min · SEPTEMBER 4, 2026
The AI readiness audit for any business process.
A 40-question audit, a weighted scoring workbook and a decision matrix that tell you which processes to automate now, which to pilot, and which to leave alone.
Score the process before you build the agent
The expensive mistake is not picking the wrong model. It is spending three months automating a process that was never ready — the data lives in someone's inbox, the rules change every quarter, and the one person who knows how it really works was not asked.
This audit is a repeatable way to check before you build. Inventory your processes, run each one through forty questions across six sections, and let a weighted score put it in one of four buckets: automate now, pilot, fix the data first, or keep it human.
By the end you will have a ranked list of candidate processes, a defensible reason for the order, a four-week pilot plan for the top one, and a one-page executive summary for whoever has to approve it.
- Category
- Toolkit
- Reading time
- 7 min
- Format
- ZIP
The things you take away from it.
Five things, listed the way they appear in the zip.
- A process inventory CSV with twelve example rows, so the first hour is filling in a structure rather than designing one
- A 40-question readiness questionnaire in six sections: data availability and quality, process definition, volume and repetition, risk and reversibility, integration surface, and people and ownership
- A scoring workbook CSV that turns the answers into a weighted readiness score and a recommendation: automate now, pilot, fix data first, or keep human
- The volume-versus-risk decision matrix, with the red flags that disqualify a process regardless of how good its score looks
- A four-week pilot plan template and a one-page executive summary template for the approval conversation
Written for three people in particular.
If none of these is you, it will still be readable — but it was written with these jobs in mind, and it assumes their problems.
Founder deciding where to start
You have a list of ten things AI could do and no principled way to pick the first, so nothing has started.
COO asked "why not use AI for this"
You need an answer that is a score with reasoning behind it, not an instinct that sounds like resistance.
Consultant qualifying an engagement
You want to find out in week one whether the data and the ownership exist, before you have committed to a delivery date.
6 chapters, in order.
Each one stands on its own. Read it front to back the first time, then come back to the chapter you need.
- 01
The process inventory
A CSV with twelve example rows covering the usual suspects — invoices, support tickets, onboarding, reporting — and the fields worth capturing before you score anything.
- 02
The 40-question audit
Six sections covering data availability and quality, process definition, volume and repetition, risk and reversibility, integration surface, and people and ownership.
- 03
The scoring workbook
How the six sections are weighted, how the answers become a single readiness score, and how the recommendation column reaches automate now, pilot, fix data first, or keep human.
- 04
The volume-versus-risk matrix
Where a process lands on the two axes that decide most of the outcome, and the red flags that override a good score outright.
- 05
The four-week pilot plan
A template for the process that scored highest: what happens each week, who owns it, and what has to be true on the last day to continue.
- 06
The executive summary
One page for the approval conversation — what you audited, what scored well, what you are asking for, and what you are deliberately not doing.
Get the full guide.
Everything above is the shape of the guide. The zip is the working version — the checklists, the thresholds and the failure modes in full. Tell us where to send it and it unlocks right here.
The AI readiness audit for any business process.
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Figures quoted in the guide.
Where a number comes from a specific engagement, the guide says so.
| Questions in the audit | 40 |
|---|---|
| Sections | 6 |
| Example processes inventoried | 12 |
| Pilot plan | 4 weeks |
High volume and low risk is not the interesting finding. The interesting finding is the process everyone wants automated that scores badly, and now you can say exactly why.
Bring the messy workflow, not the tidy one.
A working session, not a pitch. You leave with a written scope and a price, or an honest note that we are not the right people.
Questions about this download
Do I have to give my email to download this?
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It is stored against this download so we know which guide you took, and it goes on the list for the occasional related note. It is not sold, not shared with a partner, and not fed into an automated sales sequence unless you ask to talk to someone.
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Not because you downloaded a guide. If you want a conversation there is a link to book a working session on the page and you can use it; nobody chases a download. Most people who read these never speak to us, which is fine.
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Who wrote The AI readiness audit for any business process.?
The ReinforcedX delivery team — the people who have run this work in production, not a content agency. Where a figure comes from a specific engagement the guide says so, and where something is our opinion rather than a measured result it says that too.
Can I share it with my team?
Yes. Send the file around internally, put it in your wiki, quote it in a deck. For publishing extracts externally, attribute it to ReinforcedX and link back to this page.
Is this vendor-neutral or is it a pitch?
The method is neutral and works with tools we have no stake in. Where we describe how ReinforcedX does something specifically, it is labelled, so you can discount those parts. A guide that only worked if you hired us would not be worth gating.
How current is it?
The publication date is on the page. Where a claim depends on model capability or regulation that moves, the text says so rather than presenting it as settled, and guides that stop being accurate get revised rather than quietly left up.
Can we get help implementing this instead of building it ourselves?
Yes — that is the day job. The same work runs as a fixed-scope engagement: four weeks to a first system in production, measured against a quality bar agreed at kickoff, with you owning the weights, datasets, eval suites and runbooks afterwards.
What if the guide does not cover our situation?
Book a working session and describe it. If it is close to something we have delivered we will tell you what it took; if it is not, we will say so rather than stretching the guide to fit.
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