Research On Influencing Factors And Mechanism Of Human-AI Teaming Performance

AI-enabled systems(AIES)are playing an increasingly important role in organizations,bringing greater efficiency,faster and more accurate results to organizations,reducing process error rates,and effectively promoting the implementation of organizational strategies.However,many companies invest significant time,effort and resources in AIES implementation without reaping the expected benefits.Given the breadth of AIES implementation and the seriousness of the negative impact of its inability to effectively integrate with the organization,research on the factors that improve the performance of human-AI teaming is urgent.From the perspective of tasktechnology fit theory,this paper comprehensively considers the technical characteristic factors(autonomy and anthropomorphism)and employee trait factors(personal innovativeness and empathy)on human-AI teaming performance(task performance and innovative performance)Task-AI fit and task-individual fit are introduced as mediating variables.This paper enriches the research on the impact mechanism of human-AI teaming performance,and also contributes to the development of it’s measurement.The research conclusions can provide theoretical explanations for the improvement of human-AI teaming performance,and provide practical reference for the implementation of AIES in organizations.This paper adopts empirical research and collects a total of 341 valid questionnaires through online questionnaires.The test analysis was carried out by SPSS23.0 and Smart PLS3.0,and the main conclusions are as follows:(1)Both autonomy and anthropomorphism positively affect taskAI fit.Among them,sensing autonomy,thought autonomy,action autonomy,and mindless anthropomorphism have a positive impact on task-AI fit,while mindful anthropomorphism has no significant impact.(2)Personal innovativeness and empathy have a positive impact on taskindividual fit.(3)Task-AI fit and task-individual fit have a positive impact on human-AI teaming performance.Specifically,compared with task-individual fit,task-AI fit has a greater impact on task performance and less impact on innovative performance.