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AI Readiness Check
You want to use AI. Is your organisation actually ready to use it well?
A practical readiness review before AI enthusiasm turns into scattered experiments, blocked pilots or expensive tools without a clear use case.
DOES THIS SOUND FAMILIAR?
Start with what is actually happening.
- Different teams are experimenting independently.
- Security questions stop conversations before use cases are understood.
- There are dozens of ideas but no prioritisation.
- Management wants AI use cases quickly.
- People talk about models and tools more than the work that should improve.
WHAT WE NEED TO ANSWER
Good work starts with better questions.
What foundations are missing?
Which risks actually matter in your context?
Which use cases are worth testing first?
WHAT I REVIEW
The scope follows the problem.
I do not force every engagement through the same checklist. These are the areas that may matter; the agreed scope determines how deep we go.
Processes and recurring knowledge work
Data availability and sensitivity
Current tooling
Security and governance constraints
User capability and confidence
Human oversight requirements
Adoption readiness
Ability to measure value
WHAT YOU GET
Something you can use after the conversation ends.
The output should help you make a decision, change a practice or move the work forward. It should not exist simply to prove that work happened.
Readiness Assessment
Where you are ready to experiment and where basic conditions still need attention.
Opportunity Areas
The parts of work where AI could plausibly create value.
Risk & Dependency Map
Security, data, process and ownership constraints that need to be handled deliberately.
Priority Recommendations
What to explore first and what not to prioritise yet.
90-Day Starting Plan
A practical way to move from discussion to controlled learning.
HOW IT WORKS
Enough structure to make the work clear. Not so much process that the process becomes the work.
Context
We start with a short conversation about what is happening, what matters and what has already been tried.
Review
I analyse the relevant parts of the solution or operating model at the depth agreed for the engagement.
Prioritise
I organise observations around impact, risk and usefulness — not around how many issues I can find.
Walkthrough
We go through the findings together, challenge assumptions and discuss trade-offs.
Next step
You decide what happens next: implement internally, continue together or stop because the focused engagement was enough.
YOUR TIME COMMITMENT
I keep the client-side time demand deliberately light. A focused assessment usually needs a kickoff conversation, access or materials, and a final review session. We agree the exact involvement before we start.
A GOOD FIT WHEN
This is likely to help if...
- AI interest is high but direction is still unclear.
- You want to avoid buying tools before understanding use cases.
- You need business, data, risk and adoption considered together.
IT MAY NOT BE THE RIGHT FIT IF
- You already have a validated use case and only need software implementation.
- You are looking for formal legal advice on AI regulation.
If the problem is real but the format is wrong, that is useful to know early. I would rather redirect the conversation than force the challenge into the wrong service.
AI READINESS CHECK
You want to use AI. Is your organisation actually ready to use it well?
Bring me the problem, not a polished brief. A few sentences about what is happening and what you would like to change are enough to start.
Tell me what's happeningPREFER TO WRITE?
Send me a message.
You do not need a polished brief. Whether the topic is Power BI, Fabric, AI, team training, mentoring, coaching or simply a challenge that needs untangling, leave a few details and we can start from there.
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