AI is a powerful weapon to drive loyalty, increase growth and improve efficiency.
Gartner believes that 85% of customer interactions will be managed without a human by 2020 - and why not? It’s been shown that when AI is used for CX solutions, every individual customer experiences a better quality of life. You can expect growth in sales, loyalty, improvement and acceleration of decision-making and more relevant delivery of products and services. So is it time for your company to embrace the opportunities of AI? If so, you must first decide which applications to use and create a road-map to take maximum advantage.
“AI systems understand unstructured information in a way that is similar to humans. But they not only consume vast amounts of data with far greater speed, but they also learn from interactions. And because AI systems can see, talk and hear, CX teams are entering a new era: creating AI-powered experiences that feel like natural human engagement,” says IBM.
First things first - what exactly is AI?
Artificial Intelligence’s purpose is to replicate or simulate human intelligence in machines. A computer powered by AI is built to perform tasks ordinarily requiring human intelligence through machine learning, sometimes referred to as deep learning and most simplistically by a set of rules. Comprised of four categories by authors Norvig and Russell, AI has been described to; 1. Think humanly, 2. Think rationally, 3. Act humanly and 4. Act rationally. The first two are concerned with thought processes and reasoning, while the second two deal with behaviour.
Is AI already in play? Where you might have seen AI being used today:
AI has infiltrated many of our everyday lives already; Narrow AI has been described as the breakthrough of AI technology. It occurs all around us and is pretty eclectic. Sometimes we see it, and sometimes we are unaware of the impact it is already having. Visibly; Google search, image recognition software, self-driving cars, Amazons’ Alexa and Apples’ Siri. Less obvious are some of the applications powered by IBM Watson in Financial Crimes, Risk and Compliance and in areas such as disease mapping. Drone robots were birthed and manufacturing has optimised. Personal healthcare treatment recommendations and conversational bots are now used for marketing and customer service. Robo-advisors are used for stock trading and spam filters tidy our email inboxes. Social media monitors our feeds to avoid dangerous content or fake news and TV, News recommendations and song choices are being promoted via Apple News, Netflix and Spotify - to name a few.
The possibilities of AI
AI has the ability to enable brands to behave like people; when brands utilise AI within their digital platforms, more human experiences and further engagement can be obtained, and at scales once thought unimaginable. AI has the intelligence to understand customers’ feelings, express empathy, apply humour and show respect.
New ways to interact with your customers
Customers have shown willingness to embrace voice assistants and welcomed conversational commerce into their everyday lives with ease. This ‘new style’ of brand-to-consumer communication has enabled customers to connect with brands on an emotional level - anytime, anywhere, on their terms.
Although we are still very much in the infancy of this adoption, continual investment and innovation have enabled an entirely new way for brands to build value relationships with their customers. The customer’s lifestyle from marketing to sales and service can seamlessly extend across all channels.
Customer’s love voice assistants due to their speed and convenience - it has even been reported that over a third of customers would be willing to replace customer support or shop sales support with a personalised voice assistant in exchange for a faster, more convenient experience.
Beyond IA and RPA lies CX powered by AI
Automated systems can’t be hand-programmed with rules to handle every individual customer’s history. To deliver a coherent experience across all enterprise touchpoints requires finding patterns across an overwhelming number of data points requires AI.
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