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Grounded in the \u201cagentic\u201d systems delegation framework and instance-based learning theory, we employed a hidden Markov model in a longitudinal study of the dynamic delegation decision-making process involving 875 store managers. We found that there is a potential polarization in managers\u2019 delegation willingness, with managers who recognize the capability of AI exhibiting high delegation willingness and fostering increased collaboration with AI over time\u2014in contrast to their counterparts who are inclined to reduce AI\u2019s involvement. During human-AI interactions, managers\u2019 continuous performance appraisal of AI shapes their dynamic delegation willingness, which in turn affects their assessment of AI capability. This process forms a delegation feedback loop that drives the dynamics of delegation behaviors. Our study indicates that managers with a high willingness to delegate tend to outperform their counterparts and offers valuable insights for human-AI collaborative intelligence in organizational settings.<\/jats:p>","DOI":"10.25300\/misq\/2024\/18232","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T19:27:21Z","timestamp":1732044441000},"page":"1185-1204","source":"Crossref","is-referenced-by-count":2,"title":["Find the Good. 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