AI Readiness Assessment
Find out whether you're ready, before you spend.
What is AI Readiness Assessment?
Almost no AI project fails on the model. It fails because the data was a mess, because nobody owned the outcome, or because the process being automated was broken to start with.
So we look at that instead. Three weeks, six dimensions: data, skills, process, governance, infrastructure, and honest appetite for change. You get a score out of 100 and a ranked list of what to fix, in the order to fix it.
Sometimes the answer is "don't do AI yet, fix your data". We would rather say that in week two than take your money for six months and arrive at the same place.
Services provided
What the data says
Most "AI problems" turn out to be data problems wearing a hat.
The teams who get value fastest are rarely the ones with the cleverest model. They're the ones who picked a boring, well-defined process nobody enjoyed doing.
Related reading
- Business Strategy
Are You Actually AI-Ready? A Practical Readiness Check
What an AI readiness assessment should cover: five dimensions, the evidence to gather, common mistakes and how to turn a score into a costed plan.
- Technology & AI
AI-Ready Data: What It Actually Takes
What AI-ready data means in practice: ownership, fit-for-purpose quality, permissions, unstructured content, lineage and privacy, one use case at a time.
- People & Change
The AI-Ready Workforce: Upskilling at the Speed of the Technology
Building an AI-ready workforce means treating skills as infrastructure. What role-level AI upskilling involves, how to measure it, and a 90-day start.
Where Ganexa stands out
We're willing to tell you not to do it. If the data or the process isn't ready, that's the finding. It's far cheaper to hear it now.
Six dimensions, not just technology. Skills and ownership sink more projects than infrastructure ever has.
Three weeks, not a quarter. A readiness review that takes three months is a consulting project wearing a diagnostic's clothes.
Your engagement roadmap
Talk to people
1 weekWe interview the people who'd actually use the thing, not just the sponsor who asked for it. That gap is usually where the truth is.
A picture of how the work really happens.
Score it
1 weekWe assess the six dimensions against what we found, and pressure-test the use cases you're considering.
The score, and the reasoning behind each number.
The awkward conversation
2 daysWe walk you and your board through it, including the parts you won't enjoy, and agree what happens next.
A board pack and an agreed decision.
Built for where you are
Boards told to "do something about AI"
"We know we're behind. We don't know where to start and we don't want to waste a year finding out."
We give you a defensible starting point in three weeks, with the reasoning attached so it survives a challenge.
A decision, not another workshop.
Teams with a stalled pilot
"It demoed brilliantly and then never went anywhere."
Usually the pilot was fine and the surrounding data, ownership or process wasn't. We find which, and say so plainly.
You learn why it stalled, not just that it did.
What you walk away with
Readiness score
0–100 across six dimensions, with the reasoning behind every number.
Ranked fix list
What to fix first, what can wait, and what to ignore.
Use-case shortlist
The ones worth doing, with rough cost and effort. And the ones we'd drop.
Board pack
The whole thing in a form you can present without translating it first.
Ready to put AI Readiness Assessment to work?
Book a free 30-minute discovery call, you'll leave with a clear, costed next step, no obligation. Or ask us anything: we reply within one business day.
Questions we get asked about AI Readiness Assessment
How long does an AI readiness assessment take?
Three weeks: a week of interviews with the people who would use the system, a week of scoring across six dimensions, and two days to walk you and your board through the result.
What are the six dimensions you score?
Data, skills, process, governance, infrastructure, and honest appetite for change. Skills and ownership sink more projects than infrastructure does, so they carry real weight.
What do we receive at the end?
A 0–100 readiness score with the reasoning behind each number, a ranked list of what to fix first, a shortlist of use cases with rough cost and effort, and a board pack you can present as-is.
What if the answer is that we are not ready?
Then that is the finding. We would rather say "fix your data first" in week two than run a six-month programme that arrives at the same conclusion.