Observation
They sit in the data. And most organisations don't realise this until the outputs start coming back wrong.
From the Field
Looking at HR data, job titles, organisational structures, employee records, things aren't always consistent. Slight variations, duplicates, missing context. When that data is used in AI-driven outputs, those issues don't disappear. They surface immediately.
Why This Matters
AI reflects the quality of what you give it. If the data is inconsistent, the output will be too. It's often why early AI efforts lose trust, not because the model failed, but because the data wasn't ready.
Field Takeaway
If you want better outputs, start with better data.
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