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5 ways AI can turbocharge enterprise voice for a new era

Five trends spotlight how AI could revolutionize how an old technology -- voice -- will be deployed in tomorrow's work environment.

Depending on who you talk to, desk phones are one of two things: either obsolete or an essential communications tool. The truth lies somewhere in between, but there is little doubt that the conventional office desk phone is in decline. They still have a role to play, but today, desk phones are just one of several enterprise voice options. For many workers, they're trending toward being a last resort.

Yet even as the desk phone itself becomes less important, use cases for voice continue to multiply -- and many of those cases aren't necessarily tied to telephony. Until the emergence of cloud communications, voice was largely equated with telephony. The emergence of AI challenges IT leaders to broaden their thinking of how voice can bring new value to enterprises. Consider these five examples:

1. Real-time transcription

AI tools are becoming more accurate, especially with speech, and with that, this capability is a must-have for collaboration. By using AI to underpin real-time speech-to-text transcription, companies can free their workers from having to take notes in meetings, allowing them to be more present and engaged.

Workers can also use AI tools to search an entire transcript and extract only the content relevant to them, saving them additional time and effort -- especially for meetings they could not attend. Many other collaboration benefits also stem from AI-based speech-to-text services. They should be viewed as a prime value driver for the "new voice."

2. Real-time translation

This application is based on the same speech-to-text capabilities as noted above, but it focuses on a different problem: translating in real time. Most leading collaboration platforms now support dozens of languages, and more are added every day.

As the workforce becomes more globally distributed, a Tower of Babel scenario is a real concern, but with AI, comprehension barriers fall away. We're now seeing simultaneous speech-based translation, where the speaker's language can be translated to your language of choice. That means you can listen to the speaker as well as read along.

3. Touchless communications

Consumers have been doing this for years, such as using Apple's Siri for mobile search or Amazon's Alexa to check the weather before leaving home. This form of AI is called automatic speech recognition (ASR), and it has a wide range of use cases. Enterprises are seeing some adoption of Alexa and other smart speakers, but ASR is also being embedded into enterprise voice applications, like meetings, making them a touchless, pandemic-conscious experience. As AI-driven collaboration tools continue to mature, voice will be used to interface with everyday applications, among them calendars, email, and managing documents and spreadsheets.

4. Voice biometrics

Biometrics is another leading example of how voice is being used in new ways, and quite far removed from telephony. Thanks to AI, voice has become the latest form of biometrics to provide digitally-based identity validation. In addition to being faster and more accurate than conventional modes like ID badges, voice authentication is touchless, making it ideal for pandemic times.

Prime use cases include enabling individual access to controlled spaces such as buildings or meeting rooms, but it can also be used when managing how workers join meetings or access documents securely. Another valuable application is protecting privacy, preventing identity theft and deterring fraud. AI algorithms are now accurate enough to detect impersonation from bad actors, such as competitors or disgruntled ex-employees with harmful intentions.

5. Conversational AI

To date, chatbots hold limited appeal to enterprises, mainly due to their poor ASR accuracy. They're good for simple, routine queries, but little else. However, AI has improved here, progressing to the point where voice-based interactions can be conversational rather than transactional. As a result, chatbots have more understanding of context and intent, which opens the door to more precise dialogue to handle more complex tasks.

These types of chatbots can ask intelligent questions and respond to open-ended or unstructured queries. We're in the early stages of conversational AI, but this technology elevates chatbots beyond search-type inquiries, potentially enabling intelligent two-way dialogue between workers and applications.

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