Andy: Yeah, it is an awesome query. I feel as we speak synthetic intelligence is definitely capturing all the buzz, however what I feel is simply as buzzworthy is augmented intelligence. So let’s begin by defining the 2. So synthetic intelligence refers to machines mimicking human cognition. And once we take into consideration buyer expertise, there’s actually no higher instance of that than chatbots or digital assistants. Expertise that permits you to work together with the model 365 24/7 at any time that you just want, and it is mimicking the conversations that you’d usually have with a dwell human customer support consultant. Augmented intelligence however, is absolutely about AI enhancing human capabilities, growing the cognitive load of a person, permitting them to do extra with much less, saving them time. I feel within the area of buyer expertise, co-pilots have gotten a highly regarded instance right here. How can co-pilots make suggestions, generate responses, automate plenty of the mundane duties that people simply do not love to do and admittedly aren’t good at?
So I feel there is a clear distinction then between synthetic intelligence, actually these machines taking up the human capabilities 100% versus augmented, not changing people, however lifting them up, permitting them to do extra. And the place there’s overlap, and I feel we will see this pattern actually begin accelerating within the years to come back in buyer experiences is the mix between these two as we’re interacting with a model. And what I imply by that’s possibly beginning out by having a dialog with an clever digital agent, a chatbot, after which seamlessly mixing right into a human dwell buyer consultant to play a specialised function. So possibly as I am researching a brand new product to purchase reminiscent of a cellular phone on-line, I can be capable of ask the chatbot some questions and it is referring to its information base and its previous interactions to reply these. However when it is time to ask a really particular query, I is perhaps elevated to a customer support consultant for that model, simply may select to say, “Hey, when it is time to purchase, I need to make sure you’re chatting with a dwell particular person.” So I feel there’s going to be a mix or a continuum, if you’ll, of a lot of these interactions you might have. And I feel we will get to a degree the place very quickly we’d not even know is it a human on the opposite finish of that digital interplay or only a machine chatting backwards and forwards? However I feel these two ideas, synthetic intelligence and augmented intelligence are definitely right here to remain and driving enhancements in buyer expertise at scale with manufacturers.
Laurel: Properly, there’s the shopper journey, however then there’s additionally the AI journey, and most of these journeys begin with information. So internally, what’s the means of bolstering AI capabilities by way of information, and the way does information play a job in enhancing each worker and buyer experiences?
Andy: I feel in as we speak’s age, it’s normal understanding actually that AI is barely pretty much as good as the information it is educated on. Fast anecdote, if I am an AI engineer and I am attempting to foretell what films folks will watch, so I can drive engagement into my film app, I’ll need information. What films have folks watched up to now and what did they like? Equally in buyer expertise, if I am attempting to foretell the perfect end result of that interplay, I need CX information. I need to know what’s gone properly up to now on these interactions, what’s gone poorly or incorrect? I do not need information that is simply accessible on the general public web. I would like specialised CX information for my AI fashions. Once we take into consideration bolstering AI capabilities, it is actually about getting the correct information to coach my fashions on in order that they’ve these finest outcomes.
And going again to the instance I introduced in round sentiment, I feel that reinforces the necessity to make sure that once we’re coaching AI fashions for buyer expertise, it is performed off of wealthy CX datasets and never simply publicly accessible info like a number of the extra widespread giant language fashions are utilizing.
And I take into consideration how information performs a job in enhancing worker and buyer experiences. There is a technique that is vital to derive new info or derive new information from these unstructured information units that always these contact facilities and expertise facilities have. So once we take into consideration a dialog, it is very open-ended, proper? It might go some ways. It isn’t typically predictable and it is very exhausting to know it on the floor the place AI and superior machine studying methods may help although is deriving new info from these conversations reminiscent of what was the patron’s sentiment stage in the beginning of the dialog versus the tip. What actions did the agent take that both drove constructive tendencies in that sentiment or damaging tendencies? How did all of those components play out? And really shortly you may go from taking giant unstructured information units which may not have plenty of info or alerts in them to very giant information units which are wealthy and include plenty of alerts and deriving that new info or understanding, how I like to consider it, the chemistry of that dialog is taking part in a really important function I feel in AI powering buyer experiences as we speak to make sure that these experiences are trusted, they’re performed proper, they usually’re constructed on shopper information that may be trusted, not public info that does not actually assist drive a constructive buyer expertise.
Laurel: Getting again to your concept of buyer expertise is the enterprise. One of many main questions that the majority organizations face with know-how deployment is methods to ship high quality buyer experiences with out compromising the underside line. So how can AI transfer the needle on this approach in that constructive territory?
Andy: Yeah, I feel if there’s one phrase to consider with regards to AI transferring the underside line, it is scale. I feel how we consider issues is absolutely all about scale, permitting people or workers to do extra, whether or not that is by growing their cognitive load, saving them time, permitting issues to be extra environment friendly. Once more, that is referring again to that augmented intelligence. After which once we undergo synthetic intelligence pondering all about automation. So how can we provide buyer expertise 365 24/7? How can permitting customers to achieve out to a model at any time that is handy increase that buyer expertise? So doing each of these techniques in a approach that strikes the underside line and drives outcomes is vital. I feel there is a third one although that is not receiving sufficient consideration, and that is consistency. So we will enable workers to do extra. We are able to automate their duties to offer extra capability, however we even have to offer constant, constructive experiences.
