Most AI readiness assessments are sold before you can see what you’ll get. You read a proposal, maybe a one-page summary of a past engagement with the client’s name blacked out, and then you commit. It’s hard to judge the value of a deliverable you’ve never seen.
So this post does the opposite. It walks through a complete AI readiness report example, page by page: the sample report for a fictional mid-size manufacturer, which is public in full. You’ll see what each section is for, how the parts connect, and, at the end, a checklist of what any readiness report should include, whoever you buy it from or whether you build it yourself.
The company in the example
The sample is written for Example Manufacturing Co., a fictional company with 200 to 999 employees, an IT team of 6 to 20 people, Microsoft 365 as its productivity suite, Azure as its main cloud, and SOX and state privacy laws in scope. Its stated goal is to cut the time spent on service desk tickets and internal documentation. Its biggest concern is employees pasting customer and pricing data into ChatGPT. The company is fictional; the format and the reasoning are real.
The headline on page one sums up the result in one sentence: its infrastructure is ahead of its guardrails, so it should fix shadow AI and oversharing first, after which its service desk goal is very achievable. Overall score: 39 out of 100, rated Not Ready.
Section by section
How to read this report
A short orientation. It explains that the score is deterministic, that each dimension’s score is points earned over points possible, that the overall score is a plain average, and that a floor rule caps the rating if security or governance is below 40. It also explains where risks and quick wins come from and where the human judgment lives. Starting with this builds trust in everything that follows.
Executive snapshot
The whole report on one page: the score and rating, four things working in the company’s favor, four that need attention first, the first moves, and a short personal take. If a board member reads only one page, it’s this one.
Executive summary
Written for the leadership team the reader will forward it to. It explains the rating, the three issues that matter most, why the order of operations matters more than the amount of spending, and whether the stated budget is enough.
Company profile
Everything the company said about itself: size, industry, platforms, regulations, its top goal, its biggest concern, the AI tools already in use, the processes that cause the most pain, its rough budget, and what would make the report a win. Every recommendation later in the report is anchored to this page.
Scorecard
The six dimension scores on one page, as a radar chart and as bars, with the rating bands and the weakest area called out. The radar’s shape tells you where risk concentrates.
Six dimension deep dives
One chapter per dimension. Each has a one-line verdict, a narrative analysis, strengths, gaps, numbered actions under “what to do about it,” and the company’s answer to each of the four questions in that dimension. This is where most of the page count goes, and where the report stops being generic.
Top risks
Red-flag answers first, then the lowest-scoring areas. Each risk has a severity rating, its concrete impact, and a specific fix. In the sample, the top two are rated critical: overshared files becoming AI answers, and customer and pricing data going into public AI tools.
Quick wins
Low-scoring areas where the next level up is a low-effort fix, measured in weeks rather than quarters. Each quick win has an owner role, a timeframe, the steps, and the payoff. In the sample, they include publishing the acceptable use policy and baselining the service desk before any AI is introduced.
The 90-day plan
Three phases: close the risk gaps (days 1 to 30), build the foundations (days 31 to 60), and prove value with a pilot (days 61 to 90). Every action has an owner role and an expected outcome. The sequence is the point: risks close before the pilot starts, so the pilot doesn’t inherit them.
Months 4 to 12
What happens after the 90 days: scaling what the pilot proved, retiring what it didn’t, and applying the same baseline, pilot, and measure loop to the next processes on the list.
Budget guidance, measuring success, and a skills plan
Three practical chapters: how to spend the stated budget in sensible order, which numbers to track to prove the program is working, and which training and certifications fit the team’s platforms and plans.
Appendix
Every one of the 24 questions, its full 0 to 4 maturity ladder, and where the company placed. The report suggests using the ladders to set targets: the level above your current answer is next quarter’s goal.
The asset: eight things any readiness report should include
Whether you buy a report, hire a consultant, or run the assessment yourself, use this checklist to judge the result.
- Transparent scoring. You should be able to see exactly how every number was calculated and reproduce it.
- Your context, captured. Size, platforms, regulations, goals, and concerns, stated explicitly so you can check the recommendations fit.
- Ranked risks with fixes. Not a list of concerns; a ranked list with the impact and a specific fix for each.
- Quick wins with owners. Things you can start this month, assigned to roles.
- A sequenced plan. An order of operations, with owners and expected outcomes, not just a list of recommendations.
- Budget guidance tied to your actual budget, not a generic range.
- Measures of success, so you know in six months whether it worked.
- The underlying questions and your answers, so you can re-score yourself next quarter without buying the assessment again.
If a report you’re considering doesn’t do at least six of these, ask why. Consultant vs. assessment product vs. DIY and what an AI readiness assessment should cost cover how to choose.
How the score in the example is calculated
The sample’s six dimension scores are 38, 50, 50, 31, 38, and 25. Their average is 38.7, which rounds to 39 and falls in the Not Ready band. How the 0 to 100 scale works explains the math and the floor rule, and the AI readiness checklist lists all 24 questions if you’d like to score yourself.
Who a report like this is for
It’s written for IT leaders at mid-size organizations, roughly 200 to 5,000 employees, who are being asked about AI and want an honest picture before committing money. It’s most useful when you need something to take to leadership: a document that explains where you stand, what the risks are, and what the first 90 days should look like, in a form an executive can read in ten minutes and a team can execute from.
See it for yourself
Every page of the sample is public. It’s the fastest way to judge whether a report like this would be useful to your team.
Flip through the complete 38-page sample report, or download it as a PDF.
Or start with the free version, which uses 10 of the 24 questions across all six dimensions and gives you a score in a few minutes:
Get your free AI Readiness Score →
Related guides
- AI Readiness Consultant vs. Assessment Product vs. DIY
- What Should an AI Readiness Assessment Cost?
- What’s Your AI Readiness Score? How the 0–100 Scale Works
- The AI Readiness Checklist: 24 Questions to Answer Before Spending a Dollar
- The 6-Dimension AI Readiness Framework, Explained
Frequently asked questions
What does an AI readiness report include?
The sample runs to 38 pages: how to read it, an executive snapshot and summary, a company profile, a scorecard, six dimension deep dives, top risks, quick wins, a 90-day plan, a months 4 to 12 outlook, budget guidance, success measures, a skills plan, and an appendix with every question and ladder.
Is the sample AI readiness report a real company?
No. It's written for Example Manufacturing Co., a fictional mid-size manufacturer using Microsoft 365 and Azure, with SOX and state privacy laws in scope. The format and reasoning are real; the company is not.
What should any AI readiness report contain?
Transparent scoring you can reproduce, your context stated explicitly, ranked risks with specific fixes, quick wins with owners, a sequenced plan, budget guidance tied to your budget, measures of success, and the underlying questions and answers so you can re-score yourself.
Who is an AI readiness report written for?
IT leaders at mid-size organizations, roughly 200 to 5,000 employees, who are being asked about AI and want an honest picture before committing money, in a form they can take to leadership and a team can execute from.
