Andy: Yeah, it is an amazing query. I believe at this time synthetic intelligence is actually capturing the entire buzz, however what I believe 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 after we take into consideration buyer expertise, there’s actually no higher instance of that than chatbots or digital assistants. Expertise that means that you can 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 then again, is de facto about AI enhancing human capabilities, growing the cognitive load of a person, permitting them to do extra with much less, saving them time. I believe within the area of buyer expertise, co-pilots have gotten a very talked-about instance right here. How can co-pilots make suggestions, generate responses, automate numerous the mundane duties that people simply do not love to do and admittedly aren’t good at?
So I believe there is a clear distinction then between synthetic intelligence, actually these machines taking over 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 believe we’ll see this pattern actually begin accelerating within the years to return 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 resembling a mobile phone on-line, I can be capable of ask the chatbot some questions and it is referring to its data base and its previous interactions to reply these. However when it is time to ask a really particular query, I could be elevated to a customer support consultant for that model, simply would possibly 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 believe there’s going to be a mix or a continuum, if you’ll, of all these interactions you could have. And I believe we’ll get to some extent 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 believe these two ideas, synthetic intelligence and augmented intelligence are actually right here to remain and driving enhancements in buyer expertise at scale with manufacturers.
Laurel: Properly, there’s the client journey, however then there’s additionally the AI journey, and most of these journeys begin with knowledge. So internally, what’s the means of bolstering AI capabilities when it comes to knowledge, and the way does knowledge play a task in enhancing each worker and buyer experiences?
Andy: I believe in at this time’s age, it is common understanding actually that AI is just pretty much as good as the info it is educated on. Fast anecdote, if I am an AI engineer and I am attempting to foretell what motion pictures individuals will watch, so I can drive engagement into my film app, I’ll need knowledge. What motion pictures have individuals watched prior 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 knowledge. I need to know what’s gone properly prior to now on these interactions, what’s gone poorly or incorrect? I do not need knowledge that is simply obtainable on the general public web. I would like specialised CX knowledge for my AI fashions. Once we take into consideration bolstering AI capabilities, it is actually about getting the fitting knowledge to coach my fashions on in order that they’ve these greatest outcomes.
And going again to the instance I introduced in round sentiment, I believe that reinforces the necessity to make sure that after we’re coaching AI fashions for buyer expertise, it is completed off of wealthy CX datasets and never simply publicly obtainable info like a number of the extra common giant language fashions are utilizing.
And I take into consideration how knowledge performs a task in enhancing worker and buyer experiences. There is a technique that is essential to derive new info or derive new knowledge from these unstructured knowledge units that always these contact facilities and expertise facilities have. So after we take into consideration a dialog, it’s extremely open-ended, proper? It may go some ways. It’s not usually predictable and it’s extremely laborious to grasp it on the floor the place AI and superior machine studying methods may also help although is deriving new info from these conversations resembling what was the buyer’s sentiment stage at the start of the dialog versus the tip. What actions did the agent take that both drove constructive traits in that sentiment or detrimental traits? How did all of those parts play out? And really rapidly you possibly can go from taking giant unstructured knowledge units that may not have numerous info or alerts in them to very giant knowledge units which can be wealthy and include numerous alerts and deriving that new info or understanding, how I like to think about it, the chemistry of that dialog is taking part in a really vital function I believe in AI powering buyer experiences at this time to make sure that these experiences are trusted, they’re completed proper, they usually’re constructed on client knowledge that may be trusted, not public info that does not actually assist drive a constructive buyer expertise.
Laurel: Getting again to your thought of buyer expertise is the enterprise. One of many main questions that almost all organizations face with know-how deployment is find out how to ship high quality buyer experiences with out compromising the underside line. So how can AI transfer the needle on this method in that constructive territory?
Andy: Yeah, I believe if there’s one phrase to consider relating to AI shifting the underside line, it is scale. I believe how we consider issues is de facto all about scale, permitting people or staff 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 after we undergo synthetic intelligence pondering all about automation. So how can we provide buyer expertise 365 24/7? How can permitting shoppers to succeed in out to a model at any time that is handy increase that buyer expertise? So doing each of these ways in a method that strikes the underside line and drives outcomes is essential. I believe there is a third one although that is not receiving sufficient consideration, and that is consistency. So we are able to permit staff to do extra. We will automate their duties to offer extra capability, however we even have to offer constant, constructive experiences.