UMass Boston Professor’s Award-Winning Research Reveals Why Humans and AI Should Team Up to Win Over Customers
When a chatbot hands you off to a human agent - or vice versa - what happens next can make or break the customer experience.
A new study co-authored by College of Management Professor Werner H. Kunz that explores this question has just won the 2025 Best Service Article of the Year Award, the top honor given to a single paper across all major academic journals in the service research field.
Why This Matters
As companies race to deploy AI chatbots alongside human staff, most assume the goal is to make the AI as seamless - and invisible - as possible. This award-winning research overturns that assumption. Across five studies and 1,403 participants, the authors found that customers respond better when they can actually see humans and AI working together as a team, rather than having the handoffs hidden. For any business investing in AI-powered customer service, this is a rare piece of research with immediate, practical payoff: the fix isn't more AI, it's more transparency.
The paper, "The Future of Work: Understanding the Effectiveness of Collaboration Between Human and Digital Employees in Service," was published in the Journal of Service Research. It is co-authored by Khanh B. Q. Le, Laszlo Sajtos, Professor Kunz, and Karen V. Fernandez.
Kunz is a professor of marketing at UMass Boston's College of Management. His research program on human-AI collaboration in service settings continues to earn international recognition; he was named a 2025 Web of Science Highly Cited Researcher, placing him among the top 0.1% of researchers worldwide.
"We're proud to see Professor Kunz's work recognized at the highest level," said College of Management Dean Venky Venkatachalam. "His research is shaping how businesses serve their customers."
Key Research Findings
Drawing on five experimental studies involving 1,403 participants, the research demonstrates that simply making human–digital employee (HE–DE) collaboration visible to customers during service interactions strengthens perceptions of team cohesiveness and service process fluency. These perceptions, in turn, drive higher customer satisfaction.
Two specific communication strategies proved especially powerful:
- Coordination cues: clearly signaling task handovers (e.g., when a human employee transfers a request to a chatbot or vice versa).
- Team goal cues: explicitly communicating a shared objective between the human and digital team members.
Customers preferred true collaboration over models in which AI merely augments a human employee or fully substitutes for one. The advantage of collaboration stems from greater process transparency: when customers can see how the human and digital teammates work together, they experience the service as more open and coordinated.
The studies tested realistic scenarios, including prospective students seeking information about a data science program and clients interacting with a finance consulting service. Results consistently showed that transparency about roles, information flow, and joint goals created a stronger sense of a unified service team.
Practical Implications
The findings offer clear guidance for organizations integrating AI into frontline service:
- Train both human staff and chatbots to communicate handovers and shared goals openly in front of the customer.
- Design interfaces and scripts that make the collaborative process visible rather than hiding the AI "behind the scenes."
- Provide customers with summaries of interactions that document the contributions of both human and digital team members.
The authors note that making the collaboration between human and digital employees visible reinforces customers' perception of a cohesive team and a fluent service process. Pure AI self-service is not always optimal; hybrid teams that demonstrate genuine collaboration can deliver superior customer experiences.
About the Award and Paper
The Best Service Article of the Year Award recognizes the single most outstanding contribution to the service literature published in a given year. A video overview of the research findings can be viewed here.
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