Why Domain Experts Outperform Generalists on High-Stakes Data

Comparative accuracy data across healthcare, legal and financial annotation tasks, drawn from Indika program benchmarks.

The comparison

Across 14 client programs where we ran the same task through both a trained generalist pool and a licensed/certified specialist pool on a held-out sample, we measured agreement against a gold-standard adjudicated label.

The pattern holds directionally across every sector we tested, though the size of the gap tracks with how much of the task depends on tacit domain knowledge — legal clause extraction shows the widest spread, reflecting how much liability-shifting language reads as neutral to a non-lawyer.

Where the errors actually cluster

Why the gap is this large

The gap isn't about attention or effort — generalist annotators in these samples were experienced and well-trained. It's that the errors requiring correction are domain judgment calls: a negation missed in a clinical note, a liability clause that shifts risk in language a non-lawyer wouldn't flag, a risk factor that reads as neutral to anyone without underwriting experience. Generalists get the "obviously right or wrong" cases correct at close to the same rate as specialists; the entire gap lives in the ambiguous middle.

The practical implication

You don't need to route 100% of a task to specialists to close most of this gap. In our programs, routing the top 15–20% most-disagreed-upon cases (flagged by a generalist consensus-confidence score) to specialist adjudication recovers roughly 80% of the full specialist-level accuracy at a fraction of specialist-level cost.