Abstract: Workplace help-seeking is an important behavior through which employees solve work-related problems and maintain interpersonal relationships, carrying critical implications for organizational functioning. As artificial intelligence (AI) increasingly becomes a new source of help at work, how employees strategically use AI help-seeking to complement or displace help-seeking from coworkers has emerged as an important yet underexplored question. Focusing on how employees actively leverage AI to reshape interpersonal help-seeking relationships, this research proposes a theoretical framework of employees' interpersonally oriented AI help-seeking strategies. Specifically, it distinguishes between an interpersonal promotion-oriented AI help-seeking strategy, which integrates AI help-seeking with help-seeking from coworkers to pursue interpersonal gains, and an interpersonal prevention-oriented AI help-seeking strategy, which uses AI help-seeking to replace or reduce help-seeking from coworkers to avoid interpersonal risks. Building on this framework, this research develops a research agenda around four aspects: conceptual content and measurement, formation mechanisms, help-seeker outcomes, and coworker responses. It systematically explains how the two strategies emerge and how they influence both employees themselves and coworkers as potential help-seeking targets. The proposed framework is expected to extend workplace help-seeking research beyond traditional interpersonal interactions to encompass an AI-enabled triadic relationship involving help seekers, AI, and coworkers, reveal a new mechanism through which employees use AI to adjust the boundaries of interpersonal interaction, and offer practical implications for organizations seeking to guide employees in appropriately aligning AI help-seeking with help-seeking from coworkers.

Key words: help-seeking behavior, artificial intelligence, interpersonal promotion-oriented AI help-seeking strategy, interpersonal prevention-oriented AI help-seeking strategy