Abstract
PurposeAs human–AI hybrid teams become more common, it is essential for team members to interact effectively with artificial intelligence (AI) to complete tasks successfully. The integration of AI into the team environment alters the cooperative dynamics, prompting inquiry into how the design characteristics of AI impact the working mode and individual performance. Despite the significance of this issue, the effects of AI design on team dynamics and individual performance have yet to be fully explored.Design/methodology/approachDrawing upon coping theory, this study presents a research model aimed at elucidating how the characteristics of AI in human–AI interaction influence human members’ adaptive behavior, subsequently impacting individual performance. Through the creation of experiments that require human–AI collaboration to solve problems, we observe and measure various aspects of AI performance and human adaptation.FindingsWe observe that the explainability of AI enhances the behavioral adaptation of human team members, whereas the usability and intellectuality of AI improve their cognitive adaptation. Additionally, we find that human team members’ affective adaptation is negatively affected by the likability of AI. Our findings demonstrate that both behavioral and cognitive adaptations positively impact individual performance, whereas affective adaptation negatively impacts it.Practical implicationsOur research findings provide recommendations for building efficient human–AI hybrid teams and insights for the design and optimization of AI.Originality/valueOverall, these results offer insights into the adaptive behavior of humans in human–AI interaction and provide recommendations for the establishment of effective human–AI hybrid teams. These findings pioneer an understanding of how design characteristics of AI impact team dynamics and individual performance, establishing a connection between AI attributes and human adaptive behavior.
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