We've been lucky to work on numerous voice AI projects with many enterprises, Fortune 100 and fast-growing startups. We've seen patterns over the years that hinder the voice AI initiative or, even worse, push it towards failure.
Not Working Backwards from Customer
Conversational AI, and
Voice Analytics are beneficiaries of the hype. As a voice company, we cannot complain! But there exists a specific data point that we observed with almost all successful prospects. They can dive deep and explain who the customer for their voice project is, how the customer benefits from it, and how this affects the bottom and top lines of business.
The idea of owning the voice tech stack end-to-end and being able to tweak the behaviour the exact way you want is mesmerizing, right? We agree, and for many organizations, this makes sense.
Samsung own their voice AIs. But they invested in it for a decade, hired hundreds, and acquired multiple startups.
Underestimating the cost of building has two possible outcomes. Either the organization consumes the resources and has to fold or regroups and tries to buy a solution.
Open-source is great, but it is not plug-and-play. Especially not for voice AI. Why? Open source provides access to code but not the data nor expertise to work with the code. Hence if the open-source project does not satiate your requirements or if requirements change in the future, you don't have a way to proceed.
Proof-of-Concept vs Deployment
A working proof of concept within a pristine office environment doesn't mean production readiness!
Lack of Learning Loop
Once you deploy, the journey begins. It is imperative to adapt voice AI models based on users' behaviour. Time is essential. Fast iterations are the bloodline. We have built Picovoice Console to empower our customers to perform iterations instantly.