Beyond AI Buzzwords: What NENA 2025 Taught Us About Real Innovation

Insights from NENA 2025: Why "AI Everything" is Creating Confusion Instead of Solutions

Walking through the exhibition floor at NENA 2025 in Long Beach, one thing became crystal clear: artificial intelligence has officially taken over emergency communications marketing. Where three years ago only a handful of booths mentioned AI, this year virtually every vendor was promising AI-powered solutions.

But here's what we observed talking to dozens of emergency communications professionals: the AI gold rush is creating more confusion than clarity.

The "AI Everything" Problem

"Everyone is just throwing AI at you and not really giving context around what it does in the product," was a sentiment we heard repeatedly from conference attendees. The result? Decision-makers who understand their operational challenges perfectly are struggling to separate genuine innovation from marketing buzzwords.

This isn't unique to emergency communications—it's happening across every industry touched by AI. But in a field where seconds matter and accuracy is non-negotiable, the stakes of choosing the wrong solution are exponentially higher.

What We Learned from 25+ Demos

During our time at NENA 2025, we conducted over 25 product demonstrations. What struck us wasn't just the positive response, but how different our approach felt in the current landscape.

Instead of leading with AI capabilities, we focused on workflow integration. Instead of complex technical explanations, we showed simple, end-to-end solutions. Our demonstration was straightforward: a 911 call comes in, our system detects the language, provides real-time transcription and translation, and seamlessly connects to a live interpreter when needed.

The "wow factor" wasn't in the AI sophistication—it was in the practical application. Attendees could immediately see how it would work in their environment, with their existing processes, solving their specific challenges.

The Foundation Everyone Needs (But Few Talk About)

Here's something we observed while competitors focused on flashy AI features: many are building impressive displays on shaky foundations.

The reality is that any AI application in emergency communications requires the same basic building blocks:

• Listen to the call: Capture clear audio from phone systems
• Understand what's being said: Accurate transcription in real-time
• Handle multiple languages: Translate for diverse communities
• Integrate with workflows: Work within existing dispatcher processes

These aren't exciting marketing points, but they're non-negotiable technical requirements. Yet many vendors are so focused on advanced AI features that they're glossing over whether these fundamentals actually work reliably.

Responsible AI vs. AI Theater

The difference between responsible AI implementation and "AI theater" became apparent in our conversations with emergency communications professionals. They're not looking for the most sophisticated AI—they're looking for AI that reliably solves real problems.

Responsible AI in emergency communications means:

• Transparency: Users understand what the system is doing and why
• Reliability: Consistent performance under high-stress conditions
• Integration: Seamless workflow incorporation without disruption
• Control: Users maintain oversight and can intervene when needed

Compare this to AI theater, where the focus is on impressive-sounding capabilities that may not translate to practical, day-to-day operational improvements.

The Power of Listening First

One of our most valuable insights came from simply asking attendees what challenges they face that aren't being addressed. These conversations revealed innovative applications we hadn't considered.

For example, one agency mentioned the trauma of dispatchers having to view violent or disturbing multimedia messages sent to 911. Could AI help by analyzing and describing image content, allowing supervisors to gate access to disturbing visuals while still providing responders with necessary information?

This kind of innovation doesn't come from AI-first thinking; it comes from problem-first thinking, where AI becomes a tool to address real human challenges.

Cutting Through the Noise

So how do emergency communications leaders navigate the current AI landscape? Here are the key questions we recommend asking any vendor:

1. "Can you show me this working in a real workflow?"
   Demos should integrate with actual dispatcher processes, not standalone showcases.
2. "What happens when the AI gets it wrong?"
   Every AI system has failure modes. Understanding them is crucial for emergency applications.
3. "How do you handle our specific compliance requirements?"
   Generic AI solutions rarely meet the strict standards of emergency communications.
4. "Can we customize this for our unique needs?"
   Cookie-cutter AI implementations often miss the nuances of individual agencies.

The Future is Integration, Not Innovation Theater

The most effective AI implementations in emergency communications won't be the ones with the most sophisticated algorithms; they'll be the ones that seamlessly integrate into existing workflows while reliably solving specific problems.

This means moving beyond the "AI everything" approach toward thoughtful, targeted applications where artificial intelligence genuinely improves outcomes for both dispatchers and the communities they serve.

As the AI hype cycle continues, the vendors who will ultimately succeed are those who focus less on impressive technology demonstrations and more on practical, reliable solutions that work when it matters most.

The emergency communications community deserves better than buzzwords. They deserve AI that actually works.