What Happens When Machines Become Smarter? An Empirical Investigation of AI Opponents in Online Gaming

The online gaming industry increasingly incorporates virtual agents to enhance player experiences. Although prior literature has explored the provision of virtual agents in gaming, research on technological advancements remains limited. In this study, we investigate how introducing artificial intelligence (AI) powered agents as virtual opponents (versus rule-based opponents) influences human players’ engagement and performance. Leveraging a large-scale quasi-field experiment in a multiplayer online racing game, we employ difference-in-differences analyses with matching strategies and show that, on average, the introduction of AI opponents can have ‘discouragement effects’ on players, resulting in reduced player engagement and decreased performance. Our research also identifies differential long-term impacts of AI opponents on engagement and performance. In addition, our mechanism exploration reveals that introducing AI opponents increases competition intensity and immersion in the game, and these two factors exhibit opposing influences on players’ subsequent behavior. Specifically, heightened competition hinders players’ further engagement and performance progression, whereas a more immersive experience encourages more gaming participation and better performance. Further, we find the effects of AI opponents on player engagement and performance vary by player motivation and skill levels, such that competition-oriented and highly skilled players are more receptive to AI opponents. Moreover, our findings indicate that optimal engagement and performance outcomes occur when players compete against opponents with comparable and low competence levels, respectively. Lastly, we observe an inverted U-shaped relationship between the proportion of AI opponents and players’ engagement and performance, wherein both insufficient and excessive exposure to AI opponents lead to diminishing outcomes. Our study contributes to the literature on human-AI interactions by offering novel empirical evidence on the impact of AI opponents on human players’ experiential and instrumental outcomes and disentangling the underlying mechanisms. This work also offers practical implications for game designers and policymakers regarding the design of AI-integrated competitive environments.

Authors

Institutions

Publication Details

Journal
MIS Quarterly
Published
2025-08-03
DOI
https://doi.org/10.25300/misq/2025/18603
Primary Topic
Educational Games and Gamification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

What Happens When Machines Become Smarter? An Empirical Investigation of AI Opponents in Online Gaming

Haoyu Yuan, Lingli Wang, Qinglai He, Qiang Wei et al.
MIS Quarterly
Educational Games and Gamification
article

What Happens When Machines Become Smarter? An Empirical Investigation of AI Opponents in Online Gaming

Haoyu Yuan, Lingli Wang, Qinglai He, Qiang Wei, Ni Huang, Jiayin Zhang
article en

Abstract

The online gaming industry increasingly incorporates virtual agents to enhance player experiences. Although prior literature has explored the provision of virtual agents in gaming, research on technological advancements remains limited. In this study, we investigate how introducing artificial intelligence (AI) powered agents as virtual opponents (versus rule-based opponents) influences human players’ engagement and performance. Leveraging a large-scale quasi-field experiment in a multiplayer online racing game, we employ difference-in-differences analyses with matching strategies and show that, on average, the introduction of AI opponents can have ‘discouragement effects’ on players, resulting in reduced player engagement and decreased performance. Our research also identifies differential long-term impacts of AI opponents on engagement and performance. In addition, our mechanism exploration reveals that introducing AI opponents increases competition intensity and immersion in the game, and these two factors exhibit opposing influences on players’ subsequent behavior. Specifically, heightened competition hinders players’ further engagement and performance progression, whereas a more immersive experience encourages more gaming participation and better performance. Further, we find the effects of AI opponents on player engagement and performance vary by player motivation and skill levels, such that competition-oriented and highly skilled players are more receptive to AI opponents. Moreover, our findings indicate that optimal engagement and performance outcomes occur when players compete against opponents with comparable and low competence levels, respectively. Lastly, we observe an inverted U-shaped relationship between the proportion of AI opponents and players’ engagement and performance, wherein both insufficient and excessive exposure to AI opponents lead to diminishing outcomes. Our study contributes to the literature on human-AI interactions by offering novel empirical evidence on the impact of AI opponents on human players’ experiential and instrumental outcomes and disentangling the underlying mechanisms. This work also offers practical implications for game designers and policymakers regarding the design of AI-integrated competitive environments.

MIS Quarterly
University of Miami (US), Shanghai University of Finance and Economics (CN), Renmin University of China (CN), Tsinghua University (CN)
Openalex Percentile: Top 73%
Educational Games and Gamification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.