AI benchmark scores significantly overstate real-world performance because they use clean, standardized inputs and simplified environments unlike actual financial documents. In practice, models fail on messy real data, multiple formats, and document discovery tasks that benchmarks skip, causing teams to revert to manual work despite impressive headline scores.