The Real Reason 80% of AI Projects Fail (And It’s Not the Technology)
Most AI projects fail not because of bad technology, but because of a missing translator between business teams and data scientists. In retail, models with 85% accuracy are useless if they don’t understand store-specific context, customer life stages, or external variables. The real fix isn’t more data or better models—it’s a human role that converts business intuition into algorithmic features, and algorithmic outputs into actionable decisions.