When ChatGPT launched in November 2022, many companies were caught off guard – not just by its capabilities, but by how quickly it spread. Within five days, the OpenAI platform had reached one million users.
Organizations have made progress in deploying AI, but that progress should not be confused with strategic maturity. Many have optimized tools and pilots, yet few have defined how AI reshapes work, decision-making, or human interaction at scale.
The early surge of generative AI showed how quickly adoption accelerates when technology is immediately useful. Typing was the fastest gateway into early AI systems. But as AI becomes more contextual and embedded in daily work, the next shift will not be driven by better prompts. It will be driven by more natural interaction. Voice is not an add-on to this next wave. It is the interface that aligns most closely with how work actually happens.
A joint study by Jabra and The London School of Economics and Political Science found that 14% of participants preferred speaking over typing when interacting with generative AI. According to the researchers, this usage level marks the inflection point where adoption typically begins to surge.
“Most technologies hit mass adoption around the 10–15 percent mark. That is where AI sits today. When smartphones crossed that threshold, they became a general interface for getting many things done. AI is approaching the same moment. As it does, voice becomes the most natural way to access it,” said Paul Sephton, Global Head of Brand Communications at Jabra.
With voice AI expected to become a primary interface for AI interactions within the next three years, organizations should focus now on how employees adopt and use AI day to day. Success will depend less on deploying new tools and more on reducing friction, building confidence and embedding AI into natural work behaviors. Organizations that prepare for this shift early will be better positioned to drive broad employee adoption, using AI in ways that feel faster, more intuitive, and more human at scale.
The Hardware Gap: Why Voice AI Demands Different Infrastructure
Although companies have made strides in laying the ground for generative AI, voice AI is different, as it requires a full ecosystem consideration of hardware and software. As Sephton explains, with voice AI “you need to have a good audio gateway, you need to have good microphones, and good voice isolation so that the tech and the software can understand what it’s being asked.”
Yet the current AI fervor we find ourselves in has seen the majority of investment go to software, with AV having been somewhat sidelined. This comes at a cost in the era of voice AI, as audio devices that do not provide quality sound will struggle to deliver good results when using voice to work with AI tools.
Microphones without the right speech isolation and background noise reduction might capture voices from people sitting nearby, in addition to the user’s. This could cause the AI to misinterpret commands, leading to errors that require manual correction and making staff less inclined to adopt the technology.
If voice becomes the main way in which we interact with all AI, companies without the right audio gateway could be at a disadvantage in utilizing their AI investment compared to their better-prepared competitors.
Professional Audio: The Missing Link in Your AI Strategy
In the LSE study, participants were clear about their expectations. “I would want transcription accuracy to be 100% or as close to it as possible,” one participant noted. Another added that “knowing that the voice recognition is extremely accurate” would make them far more likely to integrate voice-based AI into their workflow.
This shows that good audio isn’t merely a preference, it’s essential to ushering voice AI into workflows. If every second word is misunderstood, workers will simply revert to typing, impeding the adoption of AI.
Therefore, organizations need to ensure that when employees try to interact with AI using their voice, they are able to do so seamlessly. This means equipping each area in which this exchange happens with professional-grade AV devices, like AI-ready headsets and video conferencing systems.
“If companies are investing heavily in AI services, but not the tools that deliver the return on that investment, it’s a bit like having a cart without a horse,” Sephton warns.
This becomes particularly important as AI moves from passive AI assistants undertaking transcription and distilling action items in meetings, to active AI Agents who provide more in-depth co-thinking. Future AI agents go beyond the role of tool and function more as teammates, working alongside you to not only save time, but also provide deeper intelligence and value. None of this is possible without exceptional audio quality.
Acting on the 14% Threshold
The shift to voice AI represents more than just a new interface, it marks a fundamental change in how we’ll collaborate with intelligent systems at work.
As AI agents become more autonomous and capable, voice will emerge as the natural bridge between human intention and machine action, enabling a fluid exchange that typing simply cannot match. Organizations that recognize this shift early and invest in the audio infrastructure to support it will position themselves at the forefront of this productivity revolution.
Having met the 14% threshold that puts us on the tipping point of mass adoption, the question isn’t whether voice AI will transform your workplace, but whether you’ll be ready when it does. Companies that treat audio quality as a strategic priority will unlock the full potential of their AI investments by leveraging more intuitive, efficient, and human ways of working.
