Legal Aid Chicago cuts out-of-priority intake rate from 46% to 21% with AI voice screening pilot
Legal Aid Chicago deployed Conversational AI & Chatbots for Client Intake & Matter Screening in Law Firms. As reported by www.justicebench.org: 46% → 21% out-of-priority screening rate.
Source-reported figures — cited source: www.justicebench.org
What Legal Aid Chicago was trying to fix
Legal Aid Chicago receives more than 78,000 calls per year — roughly 6,500 per month — for family law help, far more than intake staff can screen, qualify, and refer. Callers routinely hear that the queue is closed, and people who need help don't get through. Under traditional phone triage, 46% of family law callers were ultimately rejected as out-of-priority only after staff had already spent time gathering information.
What Legal Aid Chicago deployed
Legal Aid Chicago ran a three-week pilot of Haven, a commercial voice-powered AI intake assistant, on its family law line starting August 11, 2025. Calls were routed to the AI agent, which conducted conversational screening using attorney-reviewed scripts, assessed eligibility against Legal Aid Chicago's criteria, and either flagged callers for staff follow-up or provided referrals, with a staff dashboard for reviewing determinations, transcripts, and overriding AI decisions. No phone infrastructure changes were required, and the team went through 2-3 iteration cycles with Haven, including a mid-pilot redesign of the intake process itself.
Results
Over the three-week pilot, the AI handled 417 calls totaling 22+ hours, averaging 3.24 minutes each. The out-of-priority screening rate dropped from 46% under traditional triage to 21%. Of the 417 calls, 281 were screened out with referrals, 136 were screened in for further review, 44 were flagged as domestic-violence priority intakes, and 20 received specialized handling for urgent cases with court dates within a week — including one caller whose stalking and retaliation risk the AI surfaced for a same-day callback. Among callers who reached a staff follow-up, satisfaction averaged 4.1 out of 5, with 55% rating the experience 5/5.
Key Takeaways
- Structured AI questioning surfaced domestic-violence risk (e.g., stalking and retaliation) that callers hadn't disclosed through phone-menu options, and callers were more comfortable sharing sensitive details with the AI than staff expected.
- The pilot exposed pre-existing flaws in the human intake workflow — screening too many callers as eligible — prompting Legal Aid Chicago to redesign its intake questions and process mid-pilot.
- Deployment required no phone infrastructure changes but took 2-3 iteration cycles with the vendor to tune conversational flow and eligibility criteria.
Evidence for Legal Aid Chicago's Client Intake & Matter Screening deployment
- Reported outcome metrics
- 3 cited below
- Cited source
- www.justicebench.org
- Last updated
- Source link checked
Explore Related
Details
- Industry
- Law Firms
- Use Case
- Client Intake & Matter Screening
- AI Technology
- Conversational AI & Chatbots
- Company Size
- MidMarket
- Company
- Legal Aid Chicago
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