Why Who Leads a Human–Robot Team Matters

Why Who Leads a Human–Robot Team Matters

 

Robots are no longer a futuristic concept in service environments. They’re already showing up in hospitals, hotels, classrooms, and customer service settings—working alongside human employees rather than replacing them outright.

As this shift accelerates, organizations are increasingly experimenting with human–robot service teams, also known as cobotic teams. These teams combine human strengths like empathy and judgment with robotic strengths like speed, consistency, and data processing.

But as new research published in the Journal of the Academy of Marketing Science shows, how these teams are structured matters just as much as whether robots are used at all.

The Key Question

When humans and robots work together to serve customers, does it matter who’s in charge?

According to the research,Cobotic service teams and power dynamics: Understanding and mitigating unintended consequences of human‐robot collaboration in healthcare services,” by Ilana Shanks, Maura L. Scott, Martin Mende, Jenny van Doorn, and Dhruv Grewal, the answer is yes. In fact, customers care more than organizations might expect.

Across a series of studies conducted in healthcare settings, researchers found that customers respond less favorably when robots are positioned as leaders of service teams, rather than as assistants supporting human employees.

What the Research Found

About the Research

Cobotic Service Teams and Power Dynamics: Understanding and Mitigating Unintended Consequences of Human‐Robot Collaboration in Healthcare Services

Journal of the Academy of Marketing Science (JAMS), 2024

Authors:
Ilana Shank
Maura L. Scott
Martin Mende
Jenny van Doorn
Dhruv Grewal 

Download the paper >

Full Citation:

Shanks, I., Scott, M.L., Mende, M. et al. Cobotic service teams and power dynamics: Understanding and mitigating unintended consequences of human-robot collaboration in healthcare services. J. of the Acad. Mark. Sci. 53, 463–489 (2025). https://doi.org/10.1007/s11747-024-01004-1

The research examined how people react to different role assignments within cobotic teams—specifically, whether the human or the robot serves as the team leader.

The findings were consistent:

  • Customers feel less comfortable when a robot leads the team

  • Robot-led teams increase customer anxiety

  • That anxiety reduces trust, satisfaction, and willingness to return or recommend the service

Interestingly, this reaction wasn’t driven by a dislike of technology itself. Instead, it came down to power dynamics.

Why Robot Leadership Creates Discomfort

Customers tend to view robots as having less legitimate authority than humans—especially in high-stakes or personal service settings like healthcare.

When a robot is placed in a leadership role, customers:

  • Perceive the leader as less powerful or capable

  • Feel less confident in the service interaction

  • Experience higher levels of anxiety

That anxiety then spills over into behavior, shaping whether customers trust the service, follow recommendations, or want to return.

In short, robot leadership disrupts expectations about who should be in charge—and that disruption creates friction.

What Organizations Can Do Instead

The good news is that the research doesn’t suggest avoiding robots altogether. Instead, it offers clear guidance for designing cobotic teams customers are more comfortable with.

1. Position Robots as Assistants, Not Bosses

Customers respond more positively when robots are framed as:

  • Tools

  • Support systems

  • Assistants to human professionals

Keeping humans clearly in charge helps preserve trust and reduces anxiety.

2. Give Customers a Sense of Control

Even small choices can make a difference.

When customers are given options—such as choosing which robot assists them or selecting basic features—their sense of control increases, and negative reactions to robots diminish.

Control helps counterbalance discomfort.

3. Emphasize What Robots Do Well

Organizations can also improve acceptance by clearly communicating why the robot is there and what it does better than humans—such as:

  • Processing large amounts of data

  • Operating continuously

  • Performing routine or precision-based tasks

Highlighting performance capabilities helps reframe robots as valuable contributors rather than unsettling authority figures.

The research also found that customer characteristics matter.

Some customers—particularly those more comfortable with hierarchy and authority—are less likely to react negatively to robot-led teams. This opens the door for segmentation strategies and more tailored service design, especially in global or culturally diverse contexts.

The Bigger Takeaway

This research underscores a broader point for marketers, service designers, and leaders:

Technology adoption isn’t just about efficiency—it’s about experience.

As robots and AI become more embedded in service delivery, organizations must think carefully about roles, power, and perception, not just capability.

The most effective cobotic teams aren’t the ones that showcase the most advanced technology. They’re the ones designed around human expectations, comfort, and trust.

 

From the Authors

What marketing challenge(s) does your article address?

Nowadays we see more and more robots providing services, which fuels fears of “robots taking over our jobs”, for instance in service industries such as hospitality or health care. However, service environments are often too complex for robots to navigate on their own, meaning that humans and robots are likely to divide tasks, working side-by-side. According to some forecasts, around a third of current full-time occupations will be transformed into augmented services delivered by teams of humans and machines within the next 10 years – and we already see this transition now, given that many of us are nowadays co-working with AI such as Chat GPT. Given the inevitable rise of human-robot teams service customers (which we call “cobotic teams”) it is imperative to investigate how consumers react to cobotic teams, and to different role divisions within these teams.

What companies/organizations/industries will benefit from your findings?

Our findings are relevant for any/all organizations that are (considering) employing service robots. For example, healthcare organizations (hospitals, elderly care facilities), especially given the increasing staff shortages in healthcare. Another key area are hospitality services (hotel, restaurants), where service robots are more and more used. In addition, educational services, as robots are also increasingly used for instructive purposes.

Using one of the entities listed above, illustrate precisely how and to what extent it may benefit.

In a nutshell, we find that people do not like to be served by human-robot teams, and putting the robot in charge as the ‘team leader’ makes things even worse. Therefore, if a health care institution introduces a robot, the healthcare professional (e.g., nurse, physician) should always be clearly the team leader in a cobotic team.  Second, giving customers the option to choose the robot in the service team mitigates the negative effects, so giving clients a choice, for instance which color the robot has or how it should be dressed may help. Third, stressing the robot’s performance capabilities is a successful way of making people more accepting of a robot in a cobotic team. Therefore, emphasizing things the robot can do better than humans – that can be superior computing power, speaking different languages, being available 24/7 – can increase consumer acceptance of cobotic teams.

How can the recommendations from your findings specifically be implemented?

Our research has direct and actionable implications for companies as they design cobotic teams and decide on the roles robots and humans will play in these service teams. The results highlight that it is important for firms to position service robots as a “tool” or as an “assistant” that serves in a support role relative to the human service employee. Similarly, our main implications are likely to also hold true for other types of technology, such as AI or algorithms.

 

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