From the Emergency Services edition of October 30, 2026
NACo 911 workforce brief: Lyon County, Kan., AI assistant 'Betty' now handles about 35% of calls after a four-month pilot, with staff monitoring every AI interaction
National Association of Counties (NACo); Lyon County Emergency Communications Center (Kansas) · 911 emergency communications and telecommunicator workforce · United States (county case studies incl. Lyon County, Kansas)
- Publisher
- National Association of Counties
- Original publication
- 2026-10-28
- Source retrieved
- 2026-10-31
What happened
NACo's two-part 911 and behavioral health series (Oct. 28) profiles county call-handling and telecommunicator workforce practices. It states PSAPs handle more than 240 million 911 calls a year, including an estimated 24 million behavioral health calls, staffed by more than 100,000 telecommunicators, and that 68% report daily pre-shift and persistent stress. In its Lyon County, Kan., case, the emergency communications center introduced an AI assistant, 'Betty', in December 2025 for routine non-emergency calls (about 80% of volume) amid staffing shortages. After a four-month pilot it manages roughly 35% of calls; emergency calls stay human-handled and staff monitor all AI interactions. The center reports lower workload pressure, better morale, time to train two new telecommunicators, and commissioners redirected an unfilled position's funds to pay for Betty.
Why it matters
A national county association now presents a non-emergency AI call assistant as a workforce strategy, giving county leaders a peer case with a stated share of calls and a staffing-budget trade-off.
Evidence and measured results
Association case summary based on county-reported outcomes. The 35% figure has no stated denominator (all calls or non-emergency calls), period or error data; morale and workload improvements are self-reported without measurement. Vendor and cost are not given.
Limitations and uncertainty
Brief case vignette within a broader behavioral health series; figures reported by the center via NACo, not independently evaluated; 'roughly 35% of calls' is ambiguous about denominator; no misroute or caller-outcome data.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-10-30; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Small county 911 centers face staffing shortages, a thin applicant pool and high telecommunicator stress while routine non-emergency calls dominate volume.
- Stakeholders
- Emergency communications director
- Telecommunicators
- County commissioners
- County HR and budget office
- AI vendor
- Discovery questions
- What share of your call volume is routine non-emergency?
- Would you fund AI from a vacant position, and how would you revisit that?
- Who would monitor AI interactions and how much time would that take?
- Value hypothesis
- An AI assistant on non-emergency calls may free telecommunicator time for training and emergencies, as Lyon County reports, if monitoring is sustainable (interpretation).
- Potential engagement
- A call-mix and workload baseline study with a four-month pilot design and evaluation plan.
- Unsupported claims
- Accuracy of AI-handled calls
- Cost savings
- Caller satisfaction
- Transferability to large centers
Pre-sales engineering
Role takeaway
- Fit
- Fits small and mid-size PSAPs where routine non-emergency calls are most of the volume.
- Architecture and integration
- AI assistant on the non-emergency line with human handling of emergency calls and staff monitoring of every AI interaction.
- Prerequisites
- Call-type data to size the non-emergency share
- Transfer paths to telecommunicators
- Interaction logging for monitoring
- Constraints
- 35% denominator undefined
- Single small county
- Vendor not named
- Security
- Define retention and vendor access for AI call recordings and transcripts.
- Proof of value
- Baseline non-emergency share before launch
- Monitored interactions per shift
- Audited sample of AI-handled calls for errors
Delivery
Role takeaway
- Work
- Run a staged pilot with staff monitoring, then a funding and scope decision.
- Dependencies
- Vendor configuration
- County commission budget approval
- Telecommunicator monitoring time
- Ownership
- Emergency communications director, accountable to the county commission.
- Skills and adoption
- Telecommunicators learn to monitor and correct AI interactions; supervisors learn to review AI logs.
- Governance checkpoints
- End-of-pilot review before funding
- Written rule that emergency calls stay human-handled
- Periodic review of position-funding trade-off
- Acceptance criteria
- Proposed: measured share of non-emergency calls handled with a stated denominator
- Proposed: audited misroute rate below an agreed threshold
- Proposed: staff workload survey shows no increase
- Risks
- AI used to avoid hiring
- Unmeasured errors
- Monitoring fatigue
- Vendor dependence
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 sits on the non-emergency path only, with emergency calls routed to humans and every AI interaction monitored by staff.
Governance
Who approves, reviews and stays accountable for outcomes?
Shows a human-monitoring control and an explicit budget decision (repurposing an unfilled position) that county boards should document and revisit.
Security and privacy
What data, permissions and controls need testing?
Source does not describe call recording, transcript retention or vendor data access for AI-handled calls.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Frames AI as relief for a small, stressed workforce: freed time went to training new telecommunicators rather than cutting staff, though funding came from an unfilled position.
Procurement
What should contracts, pricing and exit terms secure?
Funding the tool from a vacant position is a budget precedent; boards should weigh whether it substitutes for hiring.
Operating model
Which teams own the service once it runs?
Telecommunicators shift from answering routine calls to monitoring AI interactions and handling emergencies.
Publication history
- 2026-10-30Emergency Services · Issue 545 resources
Stable resource ID: naco-911-behavioral-health-series-lyon-county-betty-ai-35pct-calls-20261028