Chapter 1 – Human Resource Management: Gaining a Competitive Advantage (HRM: Gaining a Competitive Advantage)
Chapter 4 – The Analysis and Design of Work (HRM: Gaining a Competitive Advantage)
Chapter 2 – Trends in Human Resource Management (Fundamentals of HRM)
Chapter 4 – Analyzing Work and Designing Jobs (Fundamentals of HRM)
HomeServe USA Corporation, a home-repair service company, sells plumbing, heating, cooling and electrical repair insurance plans to about five million customers in North America.
HomeServe is using an artificial intelligence-powered virtual agent known as Charlie that is based in a conversational AI platform from Google and other technologies. Machine-learning models are being used to review and analyze conversations between agents and customers. Machine learning uses data and algorithms to imitate the way that we learn, gradually improving its accuracy. In the case of HomeServe, AI can analyze the words and emotions or sentiments that customers are expressing, find patterns, and tell agents what to do next.
Charlie is currently used to assist HomeServe’s human agents. Charlie answers over eleven thousand phone calls each day, routes them to the appropriate departments, processes claims and schedules repair appointments. The agent’s gets the calls that Charlie can’t understand. She monitors agent’s phone calls whispering to them when a customer is eligible for certain coverage plans. At the start of a phone call she types on agents' screens to tell them why the customer is calling.
Charlie isn't universally liked by her human peers. She can be controlling and bossy, requiring agents to say specific words when they talk to customers. She sometimes routes callers to the wrong department. Sometimes she suggests unsolicited ideas for what agents should say to customers. For example, Charlie recently told a human agent that a customer wanted to enroll in a repair plan. She didn't understand that the man's water pipe had burst, that he was waiting for a repairperson to arrive, and was upset. When the human agent expressed his understanding to the customer (based on Charlie’s recommendation) that he wanted to enroll in a service repair plan the man became very angry. HomeServe management likes Charlie’s efficiency and customer satisfaction has increased since its use. They plan on expanding her capability by making her responsible for telling agents exactly what they should say and do next. Charlie will also start rating the human agent’s performance.
Questions for Students
- Do you think AI-powered agents like Charlie are best suited to work with expert experienced human agents, newly hired human agents, both, or neither? Explain your choice.
- Could Charlie ever replace human agents at HomeServe? Explain your position.
- Discuss the HR practices that are necessary to support the successful introduction and use of AI-powered agents like Charlie in the workplace?
Sources: IBM, “What is machine learning?”, from ibm.com/topics/machine-learning; L. Bannon, “AI Comes to the Office. It’s Bossy, Efficient & Dehumanizing”, The Wall Street Journal (February 18-19, 2023): B1, B4-B5.
Note to Instructors
An eight minute video discussing customer service, call center work (first five minutes) and the use of AI (last three minutes) from CBS Sunday Morning, “How artificial intelligence is revamping customer call centers”, is available at https://www.youtube.com/watch?v=cFK4f1t63Co. The video could be shown in-class before assigning students to teams and having them read the case and answer the questions.