Jul 10, 2025 | Read time 3 min

The ROI of every word: Why Voice AI is the next billion-dollar frontier

How real-time voice technology is unlocking new revenue, deeper engagement, and global reach for broadcasters and content creators.
Blog-The ROI of every word-V1
Tony Abrahams
Tony AbrahamsCEO, AI-Media

This time last year, voice was seen by many as a fun update to their product experience toolkit. Today, not even halfway through 2025, and it's become the cornerstone of growth strategies across a growing number of sectors. Early adopters in media have already demonstrated how voice AI can fundamentally transform business models, with others rapidly following suit.

The impact is already showing: media and entertainment is one of the top industries investing in Voice AI. From AI voiceovers to multilingual localisation, companies are using speech tech to streamline content creation and improve accessibility.

Recent reports show that AI dubbing and localisation tools are cutting production costs by up to 35%, especially for streaming and broadcast content.

What’s more, this tech is unlocking new engagement models. Broadcasters and content creators using Voice AI are accelerating time-to-air, personalising content, and expanding into new regions without increasing headcount.

As platforms scale multilingual output, audience reach and retention are becoming key benefits, with some startups reporting significant boosts to viewer engagement through automation and real-time voice personalisation.

AI Media is one of the companies leading this shift – a global voice AI powerhouse helping broadcasters and content owners scale multilingual, real-time audio experiences through automation.

In this first article in our three-part thought leadership series, Tony Abrahams – CEO and co-founder of AI Media reveals why voice represents not just the future of content delivery, but the future of revenue models.

“We’ve always believed in the power of language. But what’s happening now with voice feels different. It’s not just a feature, it’s becoming the product.

People engage with voice a lot more than they engage with text. That’s not anecdotal – we’ve run the numbers, and we estimate that the market size for voice is around 20 to 30 times that of text.

It’s a completely different opportunity. We’re leaning into this shift with LEXI Voice – a product that delivers real-time multilingual voice commentary.

The feedback has been overwhelmingly positive. Customers can see the value immediately. They want to know: if I make my content available in-language, can I reach new audiences, and can I monetise them?

If the answer is yes, that’s a compelling proposition.

This is no longer just about translating words. It’s about delivering a full experience – with tone, energy, and relevance. 

There are audiences today who want Premier League coverage in Thai, or BBC content in Spanish. And they’re not being reached.

We’re helping solve that – not just with translation, but with live commentary overlays, delivered in a way that feels right for the format and the moment.

That includes new use cases like paralinguistics – capturing emotional tone, reacting to what’s happening in the content, and matching that in real time.

To support all this, LEXI Voice draws on best-in-class components – including Speechmatics, which powers the live speech recognition layer. 

“Its real-time accuracy and ability to integrate topic models means we can tailor output to different types of content with precision.

Whether that’s rugby, weather reports, or breaking news, we can adjust spelling, pacing, and context dynamically.

That’s critical for quality and our viewers notice.

We’re making it easy for broadcasters to plug this in without changing the way they already work. It connects into our infrastructure and runs frame by frame, second by second – so it feels seamless, not separate.

As these tools continue to improve, they’re not just going to support accessibility – they’re going to be embedded by default. The better they get, the more people will use them, and the more workflows they’ll naturally be part of.

We’re already seeing that happen. Since listing on the Australian Stock Exchange in 2020, we’ve scaled to deliver 120 times more content – with basically the same revenue base. 

That tells us where this is heading: toward live, AI-driven content, delivered in any language, with any voice, anywhere in the world.

That’s not a long-term vision. It’s already happening with voice creating space for new audiences and better content experiences. And that opens up a very real commercial future."

To learn more about AI-Media or to discuss how you can power your services with their next-gen products, contact the AI-Media Team.

Latest Articles

[alt: Bilingual medical model featuring terms related to various health conditions and medications in Arabic and English. Key terms include "Chronic kidney disease," "Heart attack," "Diabetes," and "Insulin," among others, displayed in an organized layout.]
Product

Speechmatics achieves a world first in bilingual Voice AI with new Arabic–English model

Sets a new accuracy bar for real-world code-switching: 35% fewer errors than the closest competitor.

Speechmatics
SpeechmaticsEditorial Team
[alt: Illuminated ancient mud-brick structures stand against a dusk sky, showcasing architectural details and textures. Palm trees are in the foreground, adding to the setting's ambiance. Visually captures a historic site in twilight.]
Product

Your voice agent speaks perfect Arabic. That's the problem.

Most voice AI models are trained on formal Arabic, but real conversations across the Middle East mix dialects and English in ways those systems aren’t built to handle.

Yahia Abaza
Yahia AbazaSenior Product Manger
new blog image header
Technical

How Nvidia Dominates the HuggingFace Leaderboards in This Key Metric

A technical deep-dive into Token Duration Transducers (TDT) — the frame-skipping architecture behind Nvidia's Parakeet models. Covers inference mechanics, training with forward-backward algorithm, and how TDT achieves up to 2.82x faster decoding than standard RNN-T.

Oliver Parish
Oliver Parish Machine Learning Engineer
[alt: Healthcare professionals in scrubs and lab coats walk briskly down a hospital corridor. A nurse uses a tablet while others carry patient charts and attend to a gurney. The setting conveys a busy, clinical environment focused on patient care.]
Use Cases

Why AI-native EHR platforms will treat speech as core infrastructure in 2026

As clinical workflows become automated and AI-driven, real-time speech is shifting from a transcription feature to the foundational intelligence layer inside modern EHR systems.

Vamsi Edara
Vamsi EdaraFounder and CEO, Edvak EHR
[alt: Logos of Speechmatics and Edvak are displayed side by side, interconnected by a stylized x symbol. The background features soft, wavy lines in light blue, creating a modern and tech-focused aesthetic.]
Company

One word changes everything: Speechmatics and Edvak EHR partner to make voice AI safe for clinical automation at scale

Turning real-time clinical speech into trusted, EHR-native automation.

Speechmatics
SpeechmaticsEditorial Team
[alt: Concentric circles radiate outward from a central orange icon with a white Speechmatics logo. The background is dark blue, enhancing the orange glow. A thin green line runs horizontally across the lower part of the image.]
Technical

Speed you can trust: The STT metrics that matter for voice agents

What “fast” actually means for voice agents — and why Pipecat’s TTFS + semantic accuracy is the clearest benchmark we’ve seen.

Archie McMullan
Archie McMullanSpeechmatics Graduate