MCP subject-matter experts combed the recent National Emergency Number Association (NENA) trade show and conference to identify key developments and 911 modernization trends that are shaping the public safety sector. Here are their most compelling observations:
The future is being shaped by smarter artificial intelligence (AI) integration and intelligent mapping in emergency communications technology. Across multiple vendor discussions, the emphasis was less on adding isolated features and more on creating connected platforms that help telecommunicators work more efficiently to make informed decisions.
One of the 911 technology trends we witnessed was the growing role of artificial intelligence in ECCs. One vendor showcased deeper integration of its AI and CAD platforms to provide telecommunicators with conversational tools that can answer questions, clarify procedures, and provide relevant information during incidents. Rather than replacing personnel, AI is being positioned as an operational assistant that reduces cognitive workload and improves decision-making under pressure.
Advanced mapping technology also emerged as a critical innovation, especially given the growing importance of geographic intelligence in CAD environments. More accurate and capable mapping supports better decision-making and lays the foundation for additional integrated capabilities. One observed solution focuses on intuitive mapping, which enables telecommunicators to visualize incidents and dispatch directly on their maps, simplifying workflows and reducing operational complexity.
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Data integration was another major focus to make better use of the data agencies already collect. ECCs need a greater ability to extract significantly more value from emergency call data, i.e., analyzing it to provide richer operational intelligence, giving telecom operators greater situational awareness from the earliest moments of an incident.
Clearly, ECCs increasingly are operating in an ocean of data. Location information, video, text messages, vehicle telematics, alarm information, medical data, building information, sensor data, and other digital content can provide emergency responders with a much clearer understanding of what is happening before they arrive. The problem is that much of this information remains trapped in siloed systems.
Thus, the 911 community's challenge is no longer to simply generate more data. It is to determine which information is relevant, confirm its trustworthiness, and deliver it to the right person at the right moment without creating another burden.
That is where data integration becomes critical.
A telecommunicator should not have to navigate multiple screens, manually reconcile information, or serve as the human connection point between systems that cannot communicate with each other.
The future emergency response ecosystem must enable information to move across call-handling, computer-aided dispatch, geographic information, records management, and external data systems in a controlled and useful manner.
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As expected, AI discussions were pervasive, but the conversation felt different from what we heard only a few years ago, largely because AI has moved from an emerging concept to mainstream capability across the public safety ecosystem.
Consequently, the public safety sector is moving beyond asking whether AI has a role in the 911 community — that question has been answered. The more relevant questions now concern where and how it should be used, how it should be governed, and how agencies can determine whether AI is producing meaningful results.
AI-powered solutions showcased in the trade show component increasingly were focused on enhancing — not replacing — 911 professionals through applications such as:
Public safety agencies, particularly ECCs, cannot afford to deploy technology simply because it is new or impressive. They must understand how the AI solution was developed, what data it uses, how its results are validated, how it protects sensitive information, and what happens when it produces an incorrect result.
Meanwhile, solution developers need to understand that ECCs are not conventional business environments. A minor inconvenience in another industry can become a serious operational problem in an ECC.
The most encouraging aspect of the AI conversation in Columbus was its growing maturity. Agencies were asking about governance, accountability, funding, implementation, and performance — not merely requesting demonstrations. This reflects broader public safety AI adoption paired with a focus on measurable outcomes.
That's exactly where the conversation needs to be.
During an educational session, presenters described a future in which telecommunicators spend less time entering information manually and instead focus entirely on interacting with callers while AI solutions transcribe conversations, populate CAD systems, and assist in real time. While this scenario presents potential efficiency gains, significant concern exists that the 911 community will embrace these capabilities without fully understanding their implications.
For example, there is a risk of overreliance on AI-generated information. Telecommunicators and other users may come to trust AI outputs without sufficient verification, leading to "automation bias," whereby they accept AI-generated information even when it contains errors. As AI becomes more deeply integrated into workflows, this tendency could create serious operational and legal risks. Further, a growing complacency concerning automation is emerging, i.e., humans are validating their expectations instead of reviewing the output for accuracy — this will be a problem for the 911 community.
Consequently, public safety agencies need overarching governance frameworks that define how AI should be deployed, monitored, and evaluated. In other words, they must develop practical methods to ensure that human oversight remains effective throughout AI-assisted workflows.
Transparency is another major concern. Many AI solution vendors cannot clearly explain the underlying AI models powering their solutions. While public safety officials do not necessarily need deep technical knowledge to implement AI solutions effectively, they should at least be able to explain the technology they are using, how it functions, and how decisions are made. Understanding the AI model — or at minimum understanding its capabilities, limitations, and governance processes — is essential for building trust and ensuring accountability.
Speaking of accountability, as agencies increasingly deploy AI during emergency calls, citizens and elected officials inevitably will ask questions about how AI functions, where data is stored, how long information is retained, and how decisions are made. Agencies must be prepared to answer these questions clearly and honestly. In the public safety environment, AI solutions never should operate as "black boxes" because transparency is paramount to earning public trust.
As emergency communications systems become more connected, they also become more exposed. Every new interface, cloud service, data source, remote connection, and third-party technology solution expands the potential attack surface. At the same time, the mission requires systems to remain continuously available.
This creates a difficult reality: the same connectivity that enables improved situational awareness and faster emergency response also can introduce new risks.
Cybersecurity therefore cannot be added near the end of a modernization project. It must be incorporated into planning, procurement, implementation, and ongoing operations from the beginning.
Agencies also need to look beyond their own technology environments. Vendors, subcontractors, and interconnected partners can create significant third-party risk. A system is only as resilient as the ecosystem surrounding it.
The public safety sector increasingly understands this. The next step is turning awareness into sustained action, particularly for agencies that lack dedicated cybersecurity personnel.
Instead of thinking about cybersecurity, think about information assurance
These additional data sources could enable agencies to anticipate staffing needs before incidents occur rather than simply reacting after workloads increase. Although the technologies that support this capability are advancing, significant development is still needed before predictive analytics become fully mature.
Taken together, these insights from NENA 2026 spotlight 911 technology trends across emergency communications, guiding practical 911 modernization in the years ahead.
John Chiaramonte, Rich Cagle, Morgan Sava, Brian Melcer, Bonnie Maney, and Jenna Streeter contributed to this report.