As AI technology matures, businesses are leaping to include artificial intelligence in their strategic investment roadmaps. Forward-looking enterprises are especially keen to leverage AI for customer service, a cost center that traditionally scales linearly with revenue. AI-augmented customer service promises attractive efficiency gains, and have created extensive recognition. According to a study by Oracle, nearly 8 out of 10 businesses have already executed or are planning to adopt AI as a customer service solution by 2020.
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Ways of AI Usage
There are two main kinds that businesses are augmenting their customer care units with AI — “front-end AI-powered bots” and “AI-assisted human agents.” A “front-end AI-powered bot” is a conversational computer program that interacts directly with a customer without human intervention. On the other hand, an “AI-assisted human agent” is a human customer service representative who is supported by AI technology. Other terms for this model include “cyborg” or “human in the loop.” Both these models are being used in service departments across industries.
Real Time Use Case Scenarios
According to Daniel Hong Senior Product Marketing Director at /7, “front-end AI-powered chatbot” agents handle first-level queries such as FAQs. By automating responses to basic customer queries, chatbots decrease agent handle time (AHT) by 10 percent or more. They also help lessen issue escalation to higher-cost support, increase first contact resolution (FCR) rates, and reduce agent training time for basic tasks that can be handled by chatbots.
The WeChat Messenger bot deployed by China Merchant Bank — one of the largest credit card issuers in China — is another example of a front end bot. According to the AI technology provider Xiaoi, the China Merchant Bank’s front-end bot handles 1.5 to 2 million customer conversations per day, an inquiry volume that would typically require thousands of additional employees to answer. As most questions relate to card balances and payments, automation via a bot interface presents a relatively easy and cost efficient solution.
Other enterprises adopt the “AI-assisted human agent” model to reinforce their existing customer support staff. KLM, the flag carrier airline of the Netherlands, began answering customer inquiries via Facebook Messenger last year. To help reduce the average waiting period before a customer’s issue is addressed and resolved, they used DigitalGenius to provide an AI solution layer. In this model, the AI interprets the conversation and suggests response choices to the human agent. The AI adapts the reply format based on the inquiry platform — elaborating longer in an email and keeping Twitter responses to 140 characters or fewer. Rather than searching their personal knowledge base for an answer and generating a custom response each time, agents simply edit a preformed answer provided by the AI platform. The AI learns from the agents’ customizations and improves the automated answers over time.
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Answering Voice Call
This AI-assisted model is not restricted to text inquiries. Interactions, a Boston based customer Service Company, uses Natural Language Processing (NLP) to intelligently route voice calls. By using voice biometrics, they can identify 100+ features to a human voice to instantaneously validate and process a call. Mary McKenna, Director of Product Management, estimates that 30 to 50 percent of human call center activities can be streamlined with AI technology
Initial results are promising: LivePerson, a customer service platform provider, in a recent interview reports up to 35 percent efficiency gains with “AI-assisted human agent” model and DigitalGenius’s CEO Dmitry Aksenov shared that as of December 2016, 30 percent of KLM cases are resolved with the power of AI, and that percentage is on the rise.