Drafting
Efficiency gains in legal workflows
Measuring where AI actually saves time in legal work, and where it does not.
Workflow measurement framework and case study template
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Nonprofit research and education
Open research on AI in law
ACAL builds benchmarks and practical guidance to evaluate AI in legal workflows, with a focus on reliability, traceability, fairness, and privacy. Our goal is to support broader access to legal help through evidence that holds up in practice.
Featured roadmap
View allRoadmap items describe what we are building and the outputs we plan to publish. Each item is labeled by stage to make progress visible.
Designing
AI adoption patterns in law firms
Understanding adoption differences across firm sizes, practice areas, and operating models.
Survey instrument and adoption playbook outline
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Citation and source traceability in legal drafting
Developing evaluation methods for how well AI systems cite authorities and trace claims to sources.
Evaluation protocol and benchmark design notes
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