Why Voice AI is critical for enterprises in a post Covid world
Updated: Dec 31, 2020
Digital Transformation efforts in most enterprises have only gained pace as a result of the pandemic. The maxim going around in corporate circles in 2020 (and very likely to continue in 2021) is that the coronavirus was the real Chief Digital Officer (CDO) for most enterprises!! CIOs, CTOs and the CDOs today have stronger and bolder mandates to fundamentally alter the economics of their businesses.
They are increasingly being asked by their CEOs to make big bets and take on initiatives that can "materially" transform the underlying economics of their businesses.
A significant area of focus for digital enterprises is what is being referred to as "Practical AI". How businesses use AI and ML in a practical yet fundamental manner to transform themselves? Enterprises in different industries - financial services, travel, telecommunications, media and retail - are realizing that investing in strong AI & ML capabilities in their teams is critical to their post-pandemic digital future. In many Fortune 1000 companies, businesses are 'insourcing' and aggressively hiring AI & ML teams even as they outsource maintenance of legacy back-end systems to gain competitive advantage.
And one of the most practical AI applications in the enterprise is Voice AI - which refers to the use of AI & ML on voice conversations within the enterprise.
Why Voice will remain significant & relevant for the Enterprise?
Despite the proliferation of digital channels like chat/text messaging, email and social, higher value sales conversations, meetings, and involved customer service discussions are conducted pre-dominantly over voice. Speaking is not just more efficient than typing, it is also more engaging!! The human touch with voice is something that we as humans will always value. Voice is here to stay and its enduring significance is as immutable as the laws of gravity!
So what is changing in the world of Voice? It is just that the underlying plumbing is transforming - voice conversations traditionally took place over legacy telephony networks. They are quickly moving to meeting platforms like Zoom, Microsoft Teams and Webex; so a voice only conversation is being replaced by a richer voice & video conversation conducted over the internet.
The barriers historically associated with voice - costs and complexity of voice infrastructure- have been eliminated with technologies like WebRTC, 4G/5G and cloud computing. For consumers, the cost of making a voice call is now zero - it is the cost of their WiFi or 4G/5G bandwidth (as consumers use free mobile apps like Facetime, Skype and WhatsApp).
What is Voice AI? And why is it exciting?
Voice AI is highly accurate Speech-to-Text and NLU that is built on highly specialized and customizable (trainable) Deep Neural Networks running on GPUs.
What is unique about Deep Neural Networks is that the underlying Speech-to-Text and NLU models can be trained - easily and affordably - on enterprise specific datasets. You can leverage enterprise's lexicon and corpus - both voice & text. So instead of a 'one-size-fits-all approach', each enterprise can have its own Voice AI infrastructure - that is trained on its product names, industry jargon, employee & customer names, unique accents etc. Once it is trained, there are two big applications - 1) Voice AI for Automation and using 2) Voice AI for Analytics.
Voice AI for Automation
Enterprises can build Voice bots to intelligently respond to contact requests from their prospects and customers anytime anywhere. Voice Bots may also be used to respond to internal employees queries in a service/help desk context. The automation use-case is one that has really accelerated during the pandemic. Bots can help businesses deal with massive disruption caused by everyone - in sales, customer success and service - working from home during the pandemic. McKinsey has written about automation using AI.
Voice AI for Analytics
Voice AI also makes it possible for businesses to transcribe 100% of their voice conversations and subsequently mine the text for sentiment and analytics/insights.
With Voice AI, businesses can ensure that its frontline sales staff is able to pitch its core value proposition, benefits, product and service features in a consistent and compelling manner. This can be a massive boost to sales teams as they can improve conversion ratios and accurately forecast pipeline with Voice AI.
Voice AI can also ensure that customer success and service personnel are provided with tailored/customized insights to improve not just their efficiency (metrics like AHT in contact center) and but also enhance effectiveness measures like CSAT and NPS scores.
At Voicegain, we are passionate about helping enterprises, small and mid-size businesses, entrepreneurs and startup companies with their Voice AI efforts. Our mission is to build the world's most open developer friendly Voice AI platform. Be a part of our mission by signing up here. You can transcribe your calls/meetings, try out our APIs, building amazing telephony bots and more !
About the Author:
Arun Santhebennur is the Co-founder & CEO of Voicegain. To have a more in-depth conversation, please connect with Arun on LinkedIn or send us an email.