With over three decades of experience in the sector, it’s fair to say that ComputerTalk knows a thing or two about contact centers.
The CCaaS vendor has seen it all; from the evolution of IVRs in the 90s, to the birth of cloud and omnichannel offerings in the 2000s, to the popularization of CCaaS platforms in the 2010s.
And, of course, the company has been in the middle of the action during the widespread adoption of AI in recent times.
Yet, according to Chris Bardon – Chief Software Architect at ComputerTalk – AI in the customer service and experience space isn’t quite as new and shiny as people might think.
Having joined ComputerTalk with an academic background in AI, Bardon explains how the “mainstreaming” of AI in the last few years has shone a light on a lot of things that have “been around for a long, long time.”
“AI is nothing new to us. This is stuff that we've been integrating into our applications for a long time.”
That’s not to say that the technology hasn’t become more sophisticated during this period. Bardon speaks passionately about experiencing the evolution from basic AI tools to more advanced applications, such as large language models (LLMs).
Indeed, the ComputerTalk man has seen this first-hand, having watched his company expand its own AI use from technologies like speech recognition and text-to-speech, to machine learning, predictive algorithms, and automated scoring.
But how exactly has ComputerTalk managed to navigate the ever-changing world of AI-powered contact center technology?
Working Smarter and Faster
Being a part of the contact center industry during what Taylor Swift fans might call its ‘AI Era’ has not only given ComputerTalk insights into how the technology has advanced things, but it has also allowed the vendor to see how and why other companies have gotten their AI adoption wrong.
In discussing this topic, Bardon describes ComputerTalk’s approach to AI as “considered.”
He explains that while the company does move quickly, it does so in a way that allows it to maintain a wider focus, as opposed to other vendors that rushed into investing in a singular AI ‘magic bullet’.
As an example, the Software Architect recalls that when OpenAI models first launched, many vendors moved quickly to add call summarization as a standalone feature, but that was its only function.
“What we did instead is we took a look at it and realized that we could do call summarization, but we could also do all these other things.
“As a company, we always ask, ‘where can we make smart investments so that our platform is flexible?’”
This approach is visible across ComputerTalk’s entire tech stack, where the company integrates AI tools with broad utility, enabling them to be repurposed for various use cases.
This was the case with the vendor’s AI tool for document summarization. Although the solution wasn’t built specifically for legal cases, it can be applied in that context, offering more flexibility to customers.