How Can (A)I Help You?

AI that reads emotions can handle customer complaints, but it sometimes needs human assistance

Based on the research of Yifan Yu

As the saying goes, “The customer is always right.” With the proliferation of artificial intelligence in consumer-facing roles, however, that may not always be so. Some customers have figured out how to game AI chatbots, exaggerating their complaints to get bigger benefits, such as discounts.

On the plus side, however, AI customer service can help companies respond better to consumer complaints, saving money and reducing emotional burdens on human employees.

A new study by Yifan Yu, a Texas McCombs assistant professor of information, risk, and operations management, offers companies guidance on how to balance the promise and perils of AI for customer care.

With McCombs postdoctoral researcher Wendao Xue, he analyzes AI systems that detect human emotions — so-called emotion AI — and how companies might deploy them in various kinds of scenarios.

“Firms can refine how they use AI to ensure fairer, more effective decision-making,” says Yu. “Our study provides a practical framework for businesses to navigate this balance, particularly in customer care, where emotional communication plays a crucial role.”

Yu and Xue, with co-authors Lina Jia of the Beijing Institute of Technology and Yong Tan of the University of Washington, used game theory to model interactions among customers, employees, and companies. Variables included a customer’s level of emotional intensity, how much recompense an employee can offer to satisfy a customer, and costs and benefits to the company.

Overall, the analysis showed emotion AI works best for customer service when it’s integrated with human employees. Some kinds of scenarios were handled better by AI and others by people. Yu shares some principles for both.

Emotions can enhance chatbots. “Many companies already use AI to handle basic customer inquiries,” says Yu. “Adding emotion AI could help these systems better gauge frustration, confusion, or urgency.

“Instead of providing one-size-fits-all responses, the chatbot could tailor its approach based on the detected emotions, offering quicker solutions or escalating the case to another agent when needed.”

AI can play first responder. Emotion AI can decrease emotional toll and employee turnover by serving as a first point of contact with irate customers. Humans can step in when more nuance is required or when customers demand more.

Channels require different approaches. In public channels such as social media, where other users might be watching, human customer service may handle customer complaints with more sensitivity. Private channels such as customer phone calls might be a better use case for emotion AI.

Weak beats strong. Noise in the emotion AI system — random or irrelevant data — may make it harder to game the system and discourage customers from trying. Therefore, a weaker AI, with higher levels of noise in recognizing emotions, may sometimes better regulate gaming behaviors and increase the system’s social benefits.

“Normally, companies assume that better emotion recognition leads to better decisions,” Yu says. “But we found that when AI is too strong, customers are more likely to game the system by exaggerating their emotions, creating a ‘rat race’ of emotional escalation. This leads to misallocated resources and an overall loss in efficiency.”

For businesses, emotion AI could handle more than customer complaints, he says. It could help screen job candidates and monitor employees. For any of those uses, though, he recommends keeping a human component.

“AI has made remarkable strides in reasoning and problem-solving, often surpassing human capabilities in these areas,” says Yu. “But its ability to understand and respond to human emotions is still in its early stages.”

“When Emotion AI Meets Strategic Users” is published in Management Science.

Story by Suzi Morales