Why Voice AI Is the New Growth Engine for Enterprises

There’s a quiet revolution underway in enterprise tech — and you don’t need to look at a single screen to know it’s real. You can hear it.

Voice AI is no longer the stuff of smart speakers or novelty entertainment apps. It’s transforming how industries operate, how customers are served, and how employees work. From retail floors to hospital call centers to financial service hotlines, voice has become the next great growth engine. And the companies leaning in now are setting the pace for everyone else.

The Untapped Power of Enterprise Voice

Every single day, over a billion voice interactions happen inside enterprises — customer service calls, drive-thru orders, patient consultations, internal briefings. For decades, most of that valuable information disappeared the moment the conversation ended. It was insight lost forever.

That’s no longer the case. Voice AI is capturing it, understanding it, and turning it into action — in real time.

Also Read: AiThority Interview with Jonathan Kershaw, Director of Product Management, Vonage

The Voice AI Journey: From Legacy to Autonomy

In my conversations with our partners and end clients, I often describe enterprise voice adoption as a journey with five stages:

1. Legacy Systems – The era of “press 1 for…” and endless button pushing.
   If you’ve ever yelled “representative!” into a phone, you know this era well. Clunky IVR menus, long hold times, and agents scrambling to type every word you said into a ticket. It worked… kind of. But it was slow, frustrating, and blind to the real gold in those conversations — the insights we never captured.
2. Basic Speech Tech – When talking to machines still felt… weird.
   Then we got the first taste of voice recognition. You could speak commands instead of pushing buttons — but only if you said the magic words the system expected. And the voices answering back? Stiff, robotic, and about as engaging as a dial tone. It was a step forward, but it didn’t feel like talking to someone… it felt like talking to something.
3. Agent Assist – AI finally becomes a teammate.
   Things got interesting when AI stopped trying to replace humans and started helping them. Live transcription, instant info lookups, suggested answers — suddenly, agents didn’t have to juggle note-taking, system searches, and customer care all at once. They could do what they do best: listen, connect, and actually solve problems.
4. Voice AI Agents – Letting AI take some calls off our hands.
   Eventually, we let AI handle whole conversations. These voice agents could answer questions, process transactions, and work around the clock. They were a lifesaver during peak call times.
5. Agentic AI – The AI that can roll with it.
   Now we’re stepping into a whole new game. Agentic AI doesn’t just hear you — it gets you. It understands context, can adapt mid-conversation, juggle multiple steps, switch languages, and knows when to tag in a human. This is voice technology that doesn’t just answer calls; it runs part of your business, with the same judgment and agility you’d expect from your best team member.

Today, many investments are still in the early stages. But the shift is accelerating. By 2028, the leaders will be deeply invested in real-time assistance and autonomous agents. By 2030, laggards will struggle to catch up, because the competitive advantage compounds fast. Why? Because nothing else in enterprise tech is delivering this level of efficiency, cost savings, and customer experience transformation this quickly.

A Case Study in Action: Rethinking Health Insurance Service

Four years ago, one of the largest U.S. health insurers set out to completely reimagine how they serve customers. They began by modernizing their IVR and deploying chatbots to handle routine questions, instantly freeing human agents to focus on more complex needs. The next step was empowering those agents in real time.

• Phase one: automated transcription and call summaries, eliminating the grind of manual note-taking
• Phase two: a live, context-aware assistant that listens, understands, and offers on-the-spot guidance

The real breakthrough came when they cracked the problem of transcription quality. They tested multiple approaches — from internal tools to the AI Voice Platform offered by their solutions provider — across English, Spanish, and a wide range of real-world scenarios. The clear winner was the AI Voice Platform – it consistently delivered the accurate, dependable transcripts they required to make every downstream AI capability possible.

Phase one is now already in production, saving time, reducing agent burnout, and boosting customer satisfaction. Phase two is next — and it’s poised to raise the bar even higher. As their Solutions Architect put it, “The output from any AI engine is only as good as the input you feed it. For us, an accurate transcript wasn’t optional — it was mission-critical.”

What It Takes to Be Enterprise-Ready

Voice AI has to be more than “good enough” at transcription. It must:

• Operate at human-level speed
• Understand your industry’s unique vocabulary
• Speak naturally in text-to-speech
• Deploy in the cloud or on-premises
• Integrate with existing systems
• Scale across industries from healthcare to hospitality

And we’re just getting started. The next frontier is voice-to-voice AI engines that can understand words, tone, emotion, and intent without ever turning speech into text first.

It’s Time to Listen and Act

Voice AI isn’t a gimmick. It’s a strategic advantage. The organizations acting now are not only cutting costs and improving service, they’re building a foundation for agility, responsiveness, and deeper human connection.

In the future, the most successful enterprises will be the ones that didn’t just hear the opportunity — they listened.

About The Author Of This Article

Praveen Rangnath is CMO of Deepgram 

Also Read: A Pulse Check on AI in the Boardroom: Balancing Innovation and Risk in an Era of Regulatory Scrutiny