AI Agents as Team Members: Effects on Satisfaction, Conflict, Trustworthiness, and Willingness to Work With

ABSTRACT

Organizations are beginning to deploy artificial intelligence (AI) agents as members of virtual teams to help manage information, coordinate team processes, and perform simple tasks. How will team members perceive these AI team members and will they be willing to work with them? We conducted a 2 x  2 x 2 lab experiment that manipulated the type of team member (human or AI), their performance (high or low), and the performance of other team members (high or low). AI team members were perceived to have higher ability and integrity but lower benevolence, which led to no differences in trustworthiness or willingness to work with them. However, the presence of an AI team member resulted in lower process satisfaction. When the AI team member performed well, participants perceived less conflict compared to a human team member with the same performance, but there were no differences in perceived conflict when it performed poorly. There were no other interactions with performance, indicating that the AI team member was judged similarly to humans, irrespective of variations in performance; there was no evidence of algorithm aversion. Our research suggests that AI team members are likely to be accepted into teams, meaning that many old collaboration research questions may need to be reexamined to consider AI team members.

KEYWORDS:

• Artificial intelligence
• digital human
• virtual human
• collaboration technology
• algorithm aversion
• algorithm appreciation
• prescriptive agent
• workgroups
• teams

Disclosure statement

No potential conflict of interest was reported by the authors.

SUPPLEMENTARY MATERIAL

Supplemental data for this article can be accessed online at https://doi.org/10.1080/07421222.2023.2196773

Notes

¹ Soul Machines. (2022, March 3). Retrieved March 7, 2022, from https://www.soulmachines.com/

² “Autonomous humans: Technology: Digital Domain.” 2021. Digital Domain (available at https://digitaldomain.com/technology/autonomous-humans/; retrieved November 1, 2021).

Additional information

Notes on contributors

Alan R. Dennis

Alan R. Dennis ([email protected]; corresponding author) is a Professor of Information Systems and holds the John T. Chambers Chair of Internet Systems in the Kelley School of Business at Indiana University. His research focuses on four main themes: team collaboration, artificial intelligence, fake news on social media, and cybersecurity. Dr. Dennis has written more than 150 research papers and has won numerous awards for his theoretical and applied research. He is ranked the third most published Information Systems researcher over the last 30 years, and a 2020 analysis of citation data since 1990 placed him in the top 1 percent of the most influential researchers in the world, across all scientific disciplines. His research has been reported in the popular press almost 1000 times, including the Wall Street Journal, Forbes, USA Today, The Atlantic, CBS, Fox Business Network, and many others. He is a Past President, Fellow and a LEO awardee of the Association for Information Systems.

Akshat Lakhiwal

Akshat Lakhiwal ([email protected]) is an assistant professor of management information systems at the University of Georgia’s Terry College of Business. He received an MBA from the Indian Institute of Technology at New Delhi and a PhD in information systems from the Kelley School of Business, Indiana University. His research uses methodologies such as experimentation, econometrics, and machine learning to examine unintended changes in individuals’ reactions and subsequent outcomes emerging from their interaction with information technologies (ITs). He served as the managing editor for MIS Quarterly Executive and was also awarded the Doctoral Student Service Award by the Association of Information Systems in 2021. Akshat’s work has been accepted for publication in MIS Quarterly and Journal of Management Information Systems, and has also been presented at several premier conferences including the Conference on Information Systems and Technology, the Annual INFORMS Meeting, and the Neuro IS Retreat 2020.

Agrim Sachdeva

Agrim Sachdeva ([email protected]) is a Ph.D. candidate in Information Systems at the Kelley School of Business, Indiana University. His research focuses on artificial intelligence and cybersecurity, in particular on the transformation of business processes due to artificial intelligence. His research has been presented at venues such as MISQ Author Development Workshop, IEEE International Conference on Data Mining, and the Annual INFORMS Meeting.