AI adoption does not require perfect data- it requires a clear view of a decision an organisation wants to improve and the information that decision actually needs.
Why?
1. Waiting for perfect data causes paralysis.
In most cases, the data we already hold is enough to test a specific decision or prove a concept.
2. Collecting everything costs more than it delivers.
Connected data volumes are set to more than double by 2030, and unfocused collection adds storage cost, ownership confusion and compliance risk without adding value.
3. Naming the decision first makes governance and investment specific, rather than abstract.
It tells the data team exactly which assets need quality controls, and which do not.
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