AI · 1h ago
Data quality, not model choice, is the real AI failure driver
Most enterprise AI initiatives fail due to fragmented, inconsistent data rather than model flaws. Poor data governance undermines AI accuracy and business outcomes. Cleaning and structuring data is critical before deploying AI strategies.
Meridian48 take
This reframes the AI adoption narrative from model-centric to data-centric, underscoring that even the best algorithms can't fix garbage inputs.
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AI is messy: here's how to clean up your data before it derails your strategy →
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