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How legal AI is used
Prompt Engineering Impact
How prompting technique changes accuracy, completeness and relevance of legal answers.
Prompt Engineering Impact on Legal Output
How different prompting techniques affect AI accuracy, completeness, and relevance in legal tasks. Multi-step decomposition and structured output formats yield the highest quality results.
Key Takeaway
Multi-step decomposition prompts achieve 91% accuracy - a 47% improvement over basic zero-shot queries. Jurisdiction-scoped prompts achieve the highest relevance at 92%, critical for cross-border legal work.
Illustrative estimate - a directional figure for scenario framing, not a measured benchmark. Do not read these as measured per-vendor results.
Related research
Prompt Type Distribution
What lawyers ask AI to do, split across research, drafting, analysis and more.
Risk & Hallucination Rates
Estimated error rates across legal tasks, highest for citation and jurisdiction work.
Top Legal Tasks by AI Usage
The legal tasks lawyers most often hand to AI, ranked by share of usage.
Part of the HAQQ Legal AI Index
Cross-Model Benchmark
HAQQ's measured benchmark scoring legal AI models out of 50.
Legal AI Index
The full data report on how AI is used across the legal ecosystem.
Legal Agent Study
All-pass rubric grading of AI agents on long-horizon legal work.
Research Hub
Browse every legal AI research graph in one place.