AI lease abstraction accuracy depends on the tool, document type, and fields being extracted. The honest benchmark for purpose-built tools like Lextract:
Accuracy Benchmarks by Document Type
| Document Type | AI Accuracy | Notes |
|---|---|---|
| Typed NNN lease (standard) | 95–98% | Clean OCR, consistent language |
| Full service gross lease | 93–97% | More complex operating expense language |
| Modified gross lease | 92–96% | Variable structure |
| Ground lease | 85–93% | Complex cross-references |
| Lease with multiple amendments | 88–94% | Requires amendment reconciliation |
| Poor quality scan | 78–88% | OCR quality limits extraction |
For comparison, manual abstraction by a US-based paralegal achieves 85 to 92% accuracy on a first pass before quality review. AI accuracy on standard commercial leases is typically higher than manual first-pass accuracy — not lower.
What Field-Level Accuracy Means
95% accuracy on a 126-field extraction means approximately 6 fields per lease may contain an error. Not all errors are equal. An error in base rent amount has greater consequence than an error in building year built.
Confidence scoring addresses this: Lextract provides a 0–100 confidence score on every extracted field. Reviewers can immediately identify which fields are uncertain and verify only those, rather than re-reading the full document. A typical 126-field extraction with 95% accuracy has 8 to 15 fields below the 85% confidence threshold — reviewable in 10 to 20 minutes.
Where AI Is Most Accurate
- Numeric fields (rent amounts, percentages, dollar figures): Near-100% on clearly stated values
- Date fields (commencement, expiration, option deadlines): Consistently high accuracy on typed leases
- Party names (landlord, tenant, guarantor entities): High accuracy on standard formatting
- Binary clause presence (personal guarantee yes/no, audit rights yes/no): 96%+ accuracy
Where AI Is Less Accurate
- Ambiguous defined terms: Operating expense inclusions/exclusions requiring full-document context
- Amendment hierarchies: Superseded vs. current provisions in multi-amendment leases
- Complex percentage rent calculations: Variable breakpoints with sales definition carve-outs
- Handwritten annotations: Current OCR handles printed text well; handwriting accuracy is 60–80%
The Right Workflow
AI extraction as first pass with targeted human review is faster and equally accurate to full manual abstraction:
- AI processes lease in under 3 minutes (vs. 3–5 hours manually)
- Confidence scores identify 8–15 fields needing review
- Human verifies flagged fields in 15–25 minutes
- Total time: Under 30 minutes per lease vs. 3–5 hours manually
This workflow is not "trust AI blindly" — it is "trust AI for the 90% of fields that are clearly extracted and focus human attention on the 10% that warrant verification."