Editor’s note: This article is part of Police1’s “Governing AI in policing” digital report. Download the complete report here.
By Chief Christopher Ramos
Imagine dialing 911 and reporting an emergency to an artificial intelligence dispatcher so efficient that officers are already en route before you’ve finished explaining what’s happening — without you ever realizing you weren’t speaking to a human. It sounds like science fiction, but the horizon is closer than many think. While that future is not here yet, the question for law enforcement is urgent: what should agencies be doing now to prepare for it?
The dispatch challenge
For decades, dispatching has been the first and most critical link in public safety. Dispatchers answer 911 calls, interpret chaotic information and direct officers to the scene. They are the unseen lifeline connecting the public in crisis to the officers sworn to protect them. Despite advances in radios, computer-aided dispatch systems and GPS, the core model has remained largely unchanged since the 1980s. A human answers the call, enters information into a system, determines the priority and dispatches an officer.
This system has served law enforcement well, but today it is under strain. Agencies across the country face staffing shortages, high turnover and increasing call volumes. Dispatchers, working long hours at consoles, absorb a steady stream of traumatic events. Many experience burnout, stress-related health issues and symptoms associated with post-traumatic stress. At the same time, the public expects near-instant responses, consistency and compassion on every call. The gap between demand and capacity continues to widen, and the traditional dispatch model is struggling to keep up.
Artificial intelligence offers an opportunity to rethink how dispatch operates.
Why AI, and why now?
In other industries, AI is already used for real-time translation, automated transcription and even simulated customer service support. In policing, its potential lies in processing multiple calls simultaneously, cross-referencing real-time data and triaging incidents for faster, more accurate deployment of officers.
Several pilot programs across the country have begun integrating AI into call centers to manage non-emergency calls, assess urgency and route them appropriately. While these systems remain limited in scope, they demonstrate how AI can supplement human staff during staffing shortages. Their capabilities continue to evolve at a rapid pace. For law enforcement leaders, the central question is not if AI will enter the dispatch space, but how it will be implemented, regulated and trusted.
Researching the future
To explore how AI might reshape police dispatching, panels of law enforcement professionals and community members were convened in May 2025 to examine the potential benefits and risks of AI integration in 911 systems. Together, they identified more than 100 trends and dozens of possible developments that could influence the role of AI in emergency communications.
The discussions highlighted both promise and concern. AI could ease staffing shortages, improve call routing and create a more seamless connection between intake and officer deployment. At the same time, panelists expressed concern about system failures, misinterpretation of critical information, cybersecurity threats and the public’s willingness to trust a computerized voice in moments of crisis.
Despite those concerns, many participants concluded that the potential advantages of AI — if implemented carefully — outweigh the risks.
Implications for law enforcement
The implications of AI in dispatch extend beyond communication centers. If integrated thoughtfully, AI could reduce response times, improve officer safety and allow officers to spend more time on proactive policing and community engagement.
Dispatchers’ roles may also evolve. Rather than functioning solely as call takers and information relayers, they could become supervisors of advanced systems, intervening in complex or high-risk situations while AI manages more routine tasks.
However, rushed or poorly structured implementation could have serious consequences — including delayed responses, preventable harm, litigation and long-term erosion of public trust.
Community confidence will ultimately determine success. Residents must believe that AI enhances — rather than replaces — the empathy and professionalism they expect when calling for help.
A phased path forward
The future of dispatch will likely emerge gradually rather than through sudden transformation. A phased approach offers a responsible path forward:
This incremental model allows agencies to test, refine and build confidence at each stage. It reduces the likelihood of major system failures while allowing AI capabilities to expand responsibly.
Why it matters now
Dispatch is the front door of policing. It is often the first interaction between the public and law enforcement during moments of crisis. Today’s dispatchers are operating under significant strain with limited tools. Expecting the existing model to carry increasing demands indefinitely is unrealistic.
AI presents an opportunity to modernize before the system falters under its own weight. The technology will continue advancing whether law enforcement is ready or not. The choice is whether agencies shape that evolution deliberately or allow it to unfold without their direction.
Conclusion
Police dispatching stands at a crossroads. The historic model has served agencies for decades but is increasingly challenged by staffing, workload and public expectations.
Artificial intelligence offers the potential to strengthen emergency communications, making them faster, more efficient and more resilient. But success will depend on thoughtful, transparent and phased adoption — and on maintaining human judgment at the center of critical decisions.
The technology may be new. The responsibility to lead through change is not.
References
- COMTECH. How AI will enhance NG911. October 2, 2024.
- Davis E. Future of 911 dispatching with AI and machine learning. Critical Test Prep. 2023.
- Hernandez A. AI bots are helping 911 dispatchers with their workload. Stateline. 2023.
- Jamison T. Smart dispatching: How artificial intelligence is reshaping emergency response. Police1.com. 2024.
- Mandarano K. The benefits and risks of AI in 911 call centers. University of Maryland Center for Health and Homeland Security; CHHS Research. 2023.
- Neitzel L. Staffing shortages are having a negative impact on policing, but technology can help. Police1. 2023.
- Parham J. AI’s role in law enforcement: Enhancing dispatcher training with voice-enabled technology. Future Policing Institute. 2024.
- Rhye O. Revolutionizing dispatch management: The role of AI software engineers. Texta.ai Blog Articles. 2024.
- Wexler C. The revolution in emergency communications. Police Executive Research Forum. 2017.
About the author
Christopher Ramos was appointed Chief of Police for the City of Beaumont, California, effective July 16, 2025. A 20-year veteran of the Beaumont Police Department, Chief Ramos most recently served as Captain, where he led major initiatives to enhance both operational efficiency and public safety. His leadership was instrumental in launching a new Computer-Aided Dispatch (CAD) and Records Management System (RMS) and securing grant funding for a multi-million-dollar regional radio communications upgrade.
