AI Error Rates 2026: How Often AI Gets Facts Wrong -- And What It Costs

[snot]

Key Findings:

"AI hallucination rates vary from 0.7% on grounded summarization tasks to 88% on legal queries, with the Stanford HAI 2026 AI Index Report documenting sycophancy-induced hallucination rates ranging from 22% to 94% across 26 frontier models — and a 2025 mathematical proof establishing that zero-hallucination is architecturally impossible for any large language model."

Results by Domain (June 2026 Snapshot):
(Sorry I couldn't figure out how to make the spacing work in the chart below, but after each category of query listed, the first stat is the "Baseline Error Rate" and the second is the "Peak Error Rate".)

Domain Baseline Error Rate Peak Rate

Legal Research 17.3% 88.0%
Healthcare / Clinical 43.1% 64.1%
Scientific / Academic Citation 30.0% 60.0%
Financial Analysis 15.0% 25.0%
General Knowledge (conversational) 4.8% 22.0%
Code / Technical Reference 3.1% 19.1%
Grounded Summarization (RAG) 0.7% 7.6%

The article is apparently based on studies by Stanford and other reputable-sounding sources. Much more at https://axis-intelligence.com/ai-hallucination-statistics/