At CXN Live: Future of CX 2022 Andrae Kirkland, lead tech program manager at Nike and CX Network advisory board member, spoke about the power of artificial intelligence (AI) and machine learning (ML).
Kirkland outlined what he believes is the most significant application for AI and ML and explained why it is important to include humans in automated CX initiatives.
You can use AI and ML to predict customer behaviors
Kirkland explained that one of the most significant and prominent applications for AI and ML in CX is for predicting future outcomes based on current and past data. He notes that in order to leverage the predictive capabilities of AI and ML organizations need two things: large amounts of high-quality data and sufficient levels of computing power.
According to Kirkland: “AI and ML really rely on high-quality data. [So we need to ask] is it consistent and has bias been removed from the data that we have? The second piece you need is computing power. Because we have such a large amount of data we need this power to digest the information. Once you have those two, then businesses can use historical consumer and consumption data to predict consumer behavior.”
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Predicting consumer behavior is not new and it is not dependent on AI and ML, however, brands can now have more confidence in the accuracy of predictions as they are based on analysis of data sets so large that humans alone would not be able to analyze them.
Automated processes still need a human touch
While the automation of CX processes has clear benefits not all processes can be automated entirely. According to Kirkland, in some instances it is important to bring a human into the loop, for example when it is required by industry regulations, when a human is needed to verify or sign off on process steps or when it is simply the customer’s preference do deal with a human over a machine.
Kirkland explains: “When you are talking about robotic process automation or just exponential technology in general, there is this misnomer that everything can be fully automated. If I have an AI model that creates a forecast for a specific product and I am going to commit to manufacturing it, for some businesses this could cost millions of dollars. This is an example of when it would be beneficial to have a human in the loop, as you would not want to commit to that forecast without having somebody check to see if it makes sense.”
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For this reason, it is important to monitor automated CX initiatives if there is a chance that a lack of human involvement could lead to costly forecasting mistakes, broken rules or regulations or a frustrated customer.
Sign up for CXN Live: Future of CX 2022 on-demand now to hear more CX industry experts share their thoughts on what the future of CX holds.