Is AI accurate enough for your work?
The honest answer is: it depends on the field, and in the ones that matter most it is worse than it looks. Here is the real accuracy data by profession, the way AI fails in each, and how to check its output before you rely on it.
AI accuracy is not one number. The same model that answers a licensing exam correctly will invent case law, misstate a drug dose, or fabricate a financial figure when the question is open-ended and high-stakes. The gap between how confident AI sounds and how often it is right is widest in exactly the fields where being wrong is most expensive. Each page below gives you the measured accuracy, the documented failures, and a verification checklist for that field.
Accuracy by field
Is AI accurate for legal research?
General-purpose models fabricate or misstate law on most legal queries, and lawyers have been sanctioned for filing the results.
Is AI accurate for medical advice?
It passes medical exams but fails real diagnostic cases, misstates drug information, and fabricates citations that look real.
Is AI accurate for financial analysis?
Pointed at real filings it got 81 percent of questions wrong or unanswered, and fabricates figures with false precision.
Is AI accurate for coding?
It hallucinates packages that do not exist, writes code that compiles but is insecure, and makes developers more confident and less safe.
Is AI accurate for tax questions?
It answered only 39 to 47 percent of common tax questions correctly, and cites deductions and figures that no longer apply.
Is AI accurate for contract review?
The best models score at the level of a junior legal assistant on clause-level risk, and they are worst at exactly what matters most: catching a term that is missing.
Is AI accurate for journalism?
AI assistants misrepresent news content in nearly half of responses, and newsrooms that ran AI drafts unchecked published fabricated books, fake writers, and errors in over half their stories.
Is AI accurate for academic research?
AI invents citations that look completely real. In one study, only 7 percent of ChatGPT's references were both genuine and accurate.
Is AI accurate for hiring?
AI resume screeners do not invent facts, they reproduce the bias in their training data and present it as an objective score, at a scale no one reviews.
Is AI accurate for customer support?
Support bots invent policies and refunds that do not exist, and the best agents still fail more than half of realistic support tasks. Companies have been held liable for what the bot promised.
The pattern across every field
Wherever the stakes are high, the story repeats: AI produces answers that read as authoritative, cite sources that look real, and are wrong often enough that you cannot rely on any single response. The one method that consistently catches this is cross-checking the output against several independent models and treating any disagreement as a claim to verify. That is the approach behind every checklist on this site.
AI fact checker shows how multi-model verification works in practice.
Do not publish AI output on trust
Paste your draft. Four to five models check every claim in about 60 seconds, and you see exactly where they disagree before your name is on it.