From the Emergency Services edition of October 28, 2026
Brown County, Wis., dispatch puts an AI assistant on its non-emergency line, handling about 60% of those calls while humans keep all 911 calls
Brown County Public Safety Communications (Wisconsin) · 911 emergency communications and dispatch · Brown County (Green Bay area), Wisconsin, United States
- Publisher
- NBC 26 (WGBA, Green Bay)
- Original publication
- 2026-10-28
- Source retrieved
- 2026-10-29
What happened
NBC 26 reports that Brown County Public Safety Communications, which receives about 160,000 calls a year on its non-emergency number, went live this month with A.V.A. (Automated Virtual Assistant) to answer non-critical calls such as records requests and parking permits. The center spent six months adapting the tool with help from La Crosse, Waukesha and Dane County centers that already use it. Operations manager Jessica Skalecki says A.V.A. follows dispatcher operating guidelines, detects frustration or background concerns and transfers callers with a transcript, and that dispatchers monitor all A.V.A. calls in real time. The center says A.V.A. handles about 60% of non-emergency calls on average, will not replace staff, and will never answer 911 calls.
Why it matters
Another Wisconsin county joins a regional cluster of centers sharing the same non-emergency AI assistant, showing peer-to-peer adoption among U.S. PSAPs and a firm local line that 911 calls stay human.
Evidence and measured results
Local TV report quoting the operations manager and director. The 60% figure is the operator's own average from the first weeks of operation; no baseline, error rate, abandoned-call rate or staff-time saving is given, and 'overwhelmingly good response' is anecdotal.
Limitations and uncertainty
Early operator claims in the first month of live use; vendor not named in the article; 60% is an average without a defined denominator period or quality measure. Wisconsin context similar to earlier archived county deployments, so the novelty is a new jurisdiction rather than new evidence.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-10-28; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Non-emergency calls (about 160,000 a year here) pull dispatchers away from 911.
- Stakeholders
- Communications center director
- Operations manager
- County board
- Dispatcher staff and union
- Neighbouring centers already using the tool
- Discovery questions
- How many non-emergency calls do you receive and what types?
- Which neighbouring centers could share configuration or lessons?
- How would you measure containment and transfer quality?
- Value hypothesis
- AI handling of routine non-emergency calls might free dispatcher time for 911 if transfers work reliably (interpretation; the source gives no time-saved data).
- Potential engagement
- A 90-day measured pilot on one non-emergency line with baseline and transfer-quality review.
- Unsupported claims
- Staff hours saved
- Error or misrouting rates
- Caller satisfaction beyond anecdote
- Suitability for 911 calls
Pre-sales engineering
Role takeaway
- Fit
- Fits PSAPs with a distinct non-emergency number and high routine-call volume.
- Architecture and integration
- AI answers the non-emergency line, dispatchers monitor live, and transfers carry a transcript to the human.
- Prerequisites
- Separate non-emergency telephony routing
- Transcript handoff into dispatcher workstation
- Local operating guidelines encoded in call flows
- Constraints
- 911 trunks must remain human-answered
- State public-records and retention rules
- Vendor not named in source
- Security
- Limit transcript retention and vendor access; audit who reviews recorded calls.
- Proof of value
- Containment rate against defined denominator
- Share of transfers judged correct on review
- Abandoned-call and repeat-call rates versus baseline
Delivery
Role takeaway
- Work
- Configure call flows, transfer triggers and live monitoring; train dispatchers on handoffs.
- Dependencies
- Telephony configuration
- Records and permit system access
- Peer-center configuration sharing
- Ownership
- Communications center operations manager under the director.
- Skills and adoption
- Dispatchers learn to monitor AI calls and pick up transfers using transcripts.
- Governance checkpoints
- Written rule that 911 stays human
- Weekly review of transferred and failed calls
- Public notice of AI use
- Acceptance criteria
- Proposed: containment rate reported monthly with method
- Proposed: no urgent call left unescalated in audit sample
- Risks
- Urgent calls on non-emergency line missed
- Caller frustration with bot
- Overstated containment figures
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
AI answers a separate non-emergency line, with real-time dispatcher monitoring and warm transfer that passes a transcript to the human; 911 trunks are untouched.
Governance
Who approves, reviews and stays accountable for outcomes?
The center publicly commits that AI will not answer 911 calls and that staff are not being replaced; agencies can turn these into written policy and review metrics.
Security and privacy
What data, permissions and controls need testing?
Not discussed; non-emergency calls include records requests and personal details, so transcript retention and vendor access need terms.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Framed as freeing dispatchers for 911 rather than cutting jobs; callers who prefer a person can ask for a dispatcher, which matters for older or limited-English callers.
Procurement
What should contracts, pricing and exit terms secure?
Shows neighbouring-county references and shared configuration help a center adopt the same tool; buyers should still require their own performance data.
Operating model
Which teams own the service once it runs?
Splits non-emergency intake to AI with live human oversight while 911 call-taking stays fully human.
Publication history
- 2026-10-28Emergency Services · Issue 525 resources
Stable resource ID: nbc26-brown-county-dispatch-ava-ai-handles-60pct-non-emergency-calls-20261028