60-80% accuracy sounds like a passing grade until you think about what the other 20-40% actually costs.

60-80% accuracy sounds like a passing grade until you think about what the other 20-40% actually costs.

An ops team at a firm we spoke with recently had tried multiple AI tools for PDF extraction. Every one of them landed in that range. Every one of them created a new manual workflow to catch what the model missed.

That is not automation. That is automation with a shadow process attached to it.

The math is straightforward. If your team processes hundreds of documents a week and one in four needs a human to review, correct, or reclassify it, you have not reduced workload. You have shifted it downstream and made it harder to track.

Files arriving unorganized still need to be named, sorted, and extracted by hand. That work lands on the same people you were trying to free up.

The accuracy bar in wealth management operations is not 80%. It is the threshold where you can actually trust the output and remove the manual review step entirely. Anything below that just moves the problem.

What would your team do with the hours they currently spend cleaning up what the AI got wrong?