01
Focus on the outcome of “Data infrastructure”, not a generic deliverable list
We tie “Quality, access, compliance — for real use, not a pretty diagram.” to a decision-oriented summary so your team and leadership share one picture.
AI readiness audit
Data infrastructure
AI readiness audit
Is production data good enough to train a model, or just pretty on the architecture slide?
Quality, access, compliance — for real use, not a pretty diagram.
02
Time-boxed, clear criteria
Work under “Data infrastructure” in AI readiness audit uses milestones you can read in the calendar, not in slide footnotes.
03
A format the organisation can run with
You get documentation and a handover you can use next week, not a shelfware PDF.
Does this situation sound familiar?
If you recognise at least two of the following signals, the process below can help you align work and decisions.
- Stakeholders use different language for the same process around “Data infrastructure”.
- Decisions on “Data infrastructure” are delayed because scope and data are not agreed.
- You need a view on “Data infrastructure” that leadership and teams can use in the same way.
- The cost of inaction is rising faster than the cost of a structured step on “Data infrastructure”.
How we work
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Week 1
Kickoff and scope
We align the scope of “Data infrastructure”, data, interviewees, and success criteria.
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Weeks 2–3
Workshops / analysis
As needed for the offer: workshops, mapping, tests, or review — as fits “Data infrastructure”.
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Week 4+ / closure
Handover and next steps
Deliverables you can act on: what to implement, in what order, and who owns the next move.
What you get at the end
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Report / result pack
A document for “Data infrastructure” with conclusions, references to evidence we used, and recommended moves.
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Prioritised next steps (backlog)
Clarity on quick wins, items waiting on data, and items that need a leadership call.
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Handover pack
Materials your internal team can use without “consultant-only” context.
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Optional: closing workshop
One working session with owners so the meaning is shared, not only a PDF in email.
Questions we often hear
How long does this typically take?
We set scope in week one. As a guide, from a few weeks up to about three, depending on data and stakeholders.
Do you need a prior diagnosis?
We sometimes reuse an existing diagnosis. If data for “Data infrastructure” is missing, we surface that at kick-off.
Who should join from our side?
A decision owner, a topic owner, and access to the right data. We spell out names in the kickoff list.
For teams that want to make “Data infrastructure” real within AI readiness audit
If the line “Quality, access, compliance — for real use, not a pretty diagram.” matches your case, book an intro call (button below).