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AI Answers 911 Calls Amidst Staffing Crisis

August 28, 2025 Kenji Tanaka

AI is being implemented in 911 centers to handle non-emergency calls, addressing staffing shortages and improving emergency response efficiency.

AI Answers 911 Calls Amidst Staffing Crisis

911 centers across the nation are facing a critical shortage of staff, leading to increased wait times and potential delays in emergency response. To combat this issue, some jurisdictions are turning to artificial intelligence (AI) to handle non-emergency calls, allowing human dispatchers to focus on life-threatening situations.

This technological shift aims to alleviate the burden on overworked staff and improve overall efficiency in emergency response systems. Fairfax County, Virginia, is the latest to test this approach, following similar implementations in other areas.

Highlights

911 centers are severely understaffed, causing delays and increased stress for dispatchers.
AI systems are being tested to handle non-emergency calls, freeing up human operators for critical situations.
Fairfax County is the latest jurisdiction to implement AI, following examples in Arlington County and Charleston, SC.

Top 5 Key Insights

• Staffing Shortages Crisis: Emergency call centers nationwide are struggling with significant staffing shortages, leading to burnout and longer response times. This problem has been exacerbated by factors such as low pay, high stress, and negative perceptions of public safety careers.

• AI for Non-Emergency Calls: AI systems are being deployed to manage the high volume of non-emergency calls, which can account for up to 60% of total calls. These systems can provide automated assistance for inquiries such as vehicle tows and police reports, thus reducing the workload on human dispatchers.

• Faster Response Times: AI-powered systems can quickly triage calls and provide immediate responses, potentially reducing wait times for non-emergency requests. Callers can still request a live operator at any time, ensuring that human assistance remains available when needed.

• Keyword Recognition for Emergencies: AI systems are designed to recognize emergency situations by listening for specific keywords such as "someone is hurt" or "a child is missing". This ensures that urgent calls are immediately transferred to human dispatchers for appropriate action.

• Improved Resource Allocation: By automating the handling of non-emergency calls, AI allows human dispatchers to concentrate on coordinating emergency responses and providing support to those in immediate distress. This can lead to more efficient resource allocation and improved outcomes in critical situations.

Expert Insights

Dru Clarke, Assistant Director of Operations at Fairfax County's Department of Public Safety Communications Center: "We get 3,000 calls a day and approximately 60% of those calls are non-emergency calls for service... This will give them a chance to not only catch their breath but also focus on the actual emergencies".

Brian Fontes, CEO of the National Emergency Number Association: "There is an undeniable strain on the people who are the first first responders in public safety, the human voice on the line in a time of crisis... Severe staffing challenges are continuing in 911, from difficulties in hiring new personnel to problems with employee retention and a mature workforce that shows signs of stress and burnout".

Wrap Up

The integration of AI in 911 centers represents a significant step towards modernizing emergency response systems. While AI is not intended to replace human dispatchers, it can serve as a valuable tool for managing call volumes and ensuring that resources are allocated effectively.

As more jurisdictions adopt this technology, it will be crucial to monitor its impact on response times, dispatcher well-being, and overall public safety.

Author

Kenji Tanaka - A technology futurist and digital strategist based in Tokyo, specializing in emerging tech trends and their impact. He explains complex innovations and the future of digital skills for Enlightnr readers.

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