The persistent disconnection between management theories and practices has been a longstanding concern in organizational research.This disconnection becomes particularly problematic in the era of Artificial Intelligence (AI),where technological advancements are fundamentally reshaping organizational elements and logic.Conducting phenomenon-based research on human-AI collaboration has emerged as a crucial pathway for advancing theoretical development and real-world impact.

This paper begins by reviewing the current state of human-AI research,identifying three emerging themes central to understanding human-AI dynamics:human reaction to AI,human-AI interaction,and human-AI collaboration.The “human reaction to AI” theme predominantly examines individual responses to AI (and AI-generated information) during episodic interactions,characterized by vignette-based scenarios where AI does not directly impact work-related outcomes.This body of literature can be categorized into two main streams:research on AI/algorithmic decision accuracy,focusing on human assessment of computational reliability and precision; and research on AI decision legitimacy,focusing on human acceptance of moral judgment.While these studies provide valuable insights into human trust formation and AI perception,they often lack ecological validity.The “human-AI interaction” theme investigates how AI directly influences work-related outcomes,also during episodic interactions.This body of research often adopts controlled laboratory settings,exemplified by studies on ChatGPT’s impact on professional writing output and human reasoning capabilities.These studies highlight the growing relevance of AI’s immediate impact on both individual and organizational performance,emphasizing the necessity of understanding how AI interacts with human work in real-time.The “human-AI collaboration” theme addresses the evolving nature of human-AI coexistence in workplaces.AI has increasingly become embedded in work processes,creating complex,real-world challenges about how humans and AI collaborate over time.This stream of research examines dynamic,longitudinal interactions where humans and AI systems reciprocally influence outcomes across multiple dimensions,including work design,learning strategies,and long-term performance.These studies,grounded in specific organizational contexts,identify theoretical mechanisms and intervention strategies through fieldwork.

To demonstrate how phenomenon-driven research advances theoretical development,this paper analyzes an exemplary ethnographic study from the Academy of Management Journal.This study reveals how researchers can construct robust theory by systematically investigating the human-machine interface as it unfolds within authentic organizational settings.It also illuminates how richly contextualized insights from immersive fieldwork can effectively bridge theoretical development with practical implications.

After reviewing existing studies on human and AI,we further revisit seminal theories in human-computer interaction literature.These classical frameworks advocate for a system-level perspective that considers technological integration within broader institutional structures and organizational dynamics.By tracing the evolution and enduring relevance of these foundational theories,we call for a theoretical approach that recognizes the deeply embedded and interconnected nature of human-AI collaboration within complex organizational ecosystems.The goal is to inspire contemporary researchers to embrace more holistic,context-sensitive approaches when investigating emerging human-AI phenomena.

Informed by the latest studies as well as grounded in cutting-edge integration of technology and organizational settings,we here propose several promising research avenues that shed light on both theoretical advancements and managerial applications.First,we encourage exploring how employee experience and collaboration with AI jointly interact,focusing on how different experience levels impact collaboration outcomes.We should further unravel how to enable employees to maximize AI’s potential as well as alleviate the negative side.Second,we suggest that future researches may investigate how AI feedback,trust,and job security concerns affect performance in complex tasks,and how adaptation to and dependency on AI may impact employees’ skill development in the longer term.Third,we encourage researchers to examine how distinct collaboration modes between AI and humans in different contexts could optimize performance.Last,researchers can delve into users’ responses to AI suggestions and explore mechanisms to balance trust in AI and independent judgments in terms of decision-making.

The era of AI requires management scholars to bridge the gap between theory and practices by updating,transforming and transcending existing research paradigms.By uncovering deeper insights into the intricate dynamics of human-AI interaction,we shall contribute to richer and more comprehensive theoretical layers and potentially great theoretical breakthroughs.

原文引用：张志学, 高雅琪, 梁宇畅, 李涵, 李航涛, 汤明月. 人机协同时代的机遇——开展现象驱动的组织管理研究[J]. 经济管理学刊, 2024, 3(4): 65-94.

点击左下角“阅读原文”，即可下载全文PDF

（苹果系统需复制到浏览器打开）

学刊订阅方式及更多论文下载，请登录学刊官网www.qjem.cn