You've read 50 articles on AI. You've attended three webinars. Your CEO asks "where are we on AI" at every board meeting. And you still don't know where to start.
Normal. Because 90% of what's said about AI in business is noise. Generic use cases, invented ROI promises, consultants trying to sell you an audit before they even understand your business.
What you're missing isn't a tool. It's an honest framework to know if your company is actually ready, or if you're about to burn budget for nothing.
The real question isn't "should we do it"
It's "do we have the foundations for it to work".
I've seen 20-person SMEs extract massive value from AI in three weeks. And 500-employee companies blow a six-figure project because they skipped the basics.
The difference is never size. It's maturity across five very concrete axes.
The grid: 5 axes to evaluate your AI readiness
1. Does your data actually exist?
Not "we have data". Everyone has data. The question is: is it accessible, structured, and reliable?
Positive signals:
- Your business processes produce data in structured tools (CRM, ERP, ticketing system)
- Someone on the team knows where to find the data and in what format
- You've already done reporting or dashboarding on this data
Red flags:
- Your critical data lives in Excel files shared by email
- Nobody knows exactly what data you collect or where it's stored
- You have five different tools each containing a different version of the same client info
If you can't build a reliable pivot table on your data today, AI won't magically fix the problem. It'll just produce wrong results faster.
2. Do you have a concrete problem to solve?
"We want to do AI" is not a problem. It's a desire. And desires don't generate ROI.
A good starting point looks like this:
- "Our sales team spends 4 hours a week writing proposals that all look the same"
- "Our support handles 200 tickets a day, 60% of which are the same questions"
- "We lose deals because it takes us 48 hours to respond to RFPs"
If you can't state your need in one sentence with a number in it, you're not ready. You're curious. That's fine, but it's not enough to launch a project.
3. Does someone internally own the topic?
AI in business doesn't work in "buy a tool and see what happens" mode. You need someone who understands the business AND has the mandate to test, iterate, adjust.
It doesn't have to be a technical profile. It's someone who knows the processes, has the ear of leadership, and can say "let's test this for two weeks" without going through three approval committees.
No internal sponsor = no AI project. Just a subscription to a tool nobody will use in three months.
4. Are your teams ready to change their habits?
This is the axis everyone underestimates. You can have the best data, the best tool, the best use case. If the teams don't adopt it, it's dead.
Concretely:
- Have your teams already used ChatGPT or a similar tool, even informally?
- Is there resistance to change with current tools? (If the CRM migration took 18 months, AI won't be simpler.)
- Is leadership willing to free up time for training, not just send an email saying "here's the new tool"?
A reliable indicator: look at how your last tool adoption went. If it was smooth, good sign. If it was painful, expect the same level of friction with AI.
5. Do you have a realistic budget (and realistic expectations)?
Two scenarios I see on repeat:
The free fantasy: "We'll use ChatGPT and we're done." No. A ChatGPT Team subscription isn't enough to integrate AI into your processes. You need configuration time, training, sometimes custom development. Realistic minimum budget for a first project: 5K to 15K, not zero.
The mega-project fantasy: "We're launching an AI platform for the entire company." That's how you end up with a 200K project that hasn't delivered anything after six months. Start small. One process, one tool, one team. If it works, we expand.
Your readiness score
Count your "yes" answers across the five axes:
5/5: Go for it. You have the foundations, all that's missing is execution. Identify your first use case and launch a POC in two weeks.
3-4/5: You're close. There are probably one or two axes to consolidate before launching. A quick audit will keep you from going in the wrong direction.
1-2/5: Not ready, and that's OK. Invest first in your data and processes. AI will still be there in six months, and it'll be better and cheaper.
0/5: You have other priorities before AI. Solve the basics (data, tools, processes). No algorithm will compensate for an organization that doesn't know where its own information is.
What this grid doesn't replace
A tailored diagnostic. Every company has its specifics, constraints, and opportunities that five questions can't capture.
But this grid does an essential sort: it separates companies that are ready to test from those that need to lay the foundations first. And it saves you from spending money at the wrong time.
If your score is 3 or above and you want an outside perspective to identify the right first project, let's talk.
Thirty minutes, no slides, no pitch. Just an honest conversation to see if AI can actually gain you something.