The terms “artificial intelligence,” or AI, and “machine learning” are thrown about a lot these days in conjunction with business software or mobile technology. Many of us still understand the word fodder for science fiction, but we DID watch IBM’s Watson computer win at Jeopardy! just a few years ago. So it unreasonable to expect that marketing claims about AI in our contact center solutions are real?
Yes, probably. What gets billed as AI very often turns out to be machine learning, and most of us are familiar with the latter because of using Siri, Alexa or any of the other digital personal assistants available today. While these machine learning solutions can certainly be “smart” on occasion, they’ve yet to become the equivalent of a human personal assistant in anticipating our needs. In a recent blog post, Aspect’s Tobias Goebel warned of the danger of over-using terms like AI and machine learning for what should be simply good software design.
“Things get problematic when developers over-promise AI performance and it under-delivers at launch time,” he wrote. “If it gets better with use, how good is it when I start using it? Does it provide enough value out of the box that I am willing to keep using it to ultimately reap the rewards?”
After all, you’re not participating in a beta test…you just shelled out valuable cash for what you’re assuming is a mature product, and you certainly don’t want to put your customers in the hands of a contact center solution that’s the equivalent of a student driver on the highway.
Goebel noted that grand claims of AI or even machine learning may be taking the place of good old thoroughness and user-centric design.
“If we want personal assistants or similar technology to succeed, we cannot rely on machine learning alone, not right from the start,” he wrote. “Software developers (rather: designers) need to ‘digitize’ our lives, meticulously defining rules that describe how we go about our daily lives, so that the little helpers can truly assist us through it, helping like a human would.”
Machine learning can certainly greatly enhance a contact center solution, but buyers shouldn’t assume that it’s going to suddenly fit their business to a “T” after handling a few customer interactions, and they shouldn’t be sold into the idea that machine learning will replace good software design.
“Each and every step needs to be designed and considered, converted into rules and decision trees,” wrote Goebel. “Machine learning can then come on top to improve the processes over time, and yes, maybe ‘get to know me over time’ – over time, but not on day one.”
This topic and more will be explored in great detail at the upcoming ITEXPO. The session, How AI is changing the Customer Experience, could be a nice place to start. See you in sunny South Florida!