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Artificial intelligence (AI) advancements enable humans and AI agents to collaborate as human-AI teams, enhancing performance, decision-making, and problem-solving. Despite its significance for IS researchers, the field lacks a cohesive scientific dialogue due to scattered research and varied definitions. This study systematically explores human-AI teaming (HAIT) through morphological analysis to map the relevant conceptual constituents of this phenomenon. Our findings are presented in a morphological box, categorizing human-AI teaming along multiple dimensions derived from qualitative literature insights. These dimensions and their characteristics offer a detailed explication of previously latent constituents of the phenomenon, addressing the need for a holistic understanding. This research encourages deeper theoretical engagement and more precise conceptualization within the field by providing a conceptual framework, fostering discourse formation on human-AI teaming.

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The Core Building Blocks of Human-AI Teaming: Conceptualization and Typology Development

  • 会议论文

  • 发表日期：

    2025年

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  • Tim-Christoph Engelhardt,
  • Benjamin Mueller,
  • Julia M. Kensbock

摘要

Artificial intelligence (AI) advancements enable humans and AI agents to collaborate as human-AI teams, enhancing performance, decision-making, and problem-solving. Despite its significance for IS researchers, the field lacks a cohesive scientific dialogue due to scattered research and varied definitions. This study systematically explores human-AI teaming (HAIT) through morphological analysis to map the relevant conceptual constituents of this phenomenon. Our findings are presented in a morphological box, categorizing human-AI teaming along multiple dimensions derived from qualitative literature insights. These dimensions and their characteristics offer a detailed explication of previously latent constituents of the phenomenon, addressing the need for a holistic understanding. This research encourages deeper theoretical engagement and more precise conceptualization within the field by providing a conceptual framework, fostering discourse formation on human-AI teaming.