- Your processes and data: where it lives, who owns it, what state it is in
- The AI tools your team already uses, approved or not
- Data protection: what GDPR, Saudi PDPL or UAE PDPL mean for each idea
- The three to five uses worth doing, each with an estimated cost and return
- The ideas worth dropping, and why
Services · AI Readiness Audit
2 min read ·The AI Readiness Audit is a two-week assessment that maps where your data lives, what may safely leave the company and which uses of AI will earn back their cost, delivered as a document your board can act on. Two weeks to answer "what should we do with AI?" properly. I map where your data really lives, what may safely leave the building, and the few uses of AI that will earn back their cost. You get a document your board can act on, with no obligation to build it with me.
A written report and a costed roadmap, in English or Arabic, plus a presentation for your leadership. Every recommendation says what it needs, what it risks and how you will know it worked.
I build and run AI features on real customer data, so the roadmap is grounded in what is actually buildable: redaction, evaluation tests, logging and the cases where the machine should not speak at all.
Usually. The AI Use Check (one week) covers what your team already does with AI, what data is leaving and the three rules to set now. The Audit is the upgrade when you want the full picture and a costed roadmap.
No. Finding out what state your data is in is part of the audit.
It suits teams from about 20 people up. For a smaller team or a single question, the Diagnosis is usually the better start.
Not unless you agree to it in writing. I can work on your infrastructure or on anonymised samples.
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