What Types of Human-AI Teams Exist?

2026-07-02

AI Summary

Existing research on human-AI collaboration lacks a systematic typology of teams, hindering the comparability and generalizability of findings. Addressing this gap, this study draws on psychological team theory to conduct a qualitative cluster analysis of 53 relevant publications and proposes, for the first time, a five-category framework for human-AI teams: AI-as-assistant, ad-hoc dependence, enforced dependence, dyadic equality, and collective equality. This typology clarifies fundamental structural differences across studies, revealing significant heterogeneity in the field. To support its adoption, the work also provides a practical identification guide and a reporting checklist, thereby facilitating systematic integration and theoretical advancement in human-AI collaboration research.

Abstract

Human-AI teaming has received increasing attention in the literature. However, the range of studies conducted in multiple domains make it difficult to understand what types of teams are being studied, and in what ways are they similar/different from one another. In this study, we analyse 53 papers on human-AI teams and categorise them into five main clusters based on psychological taxonomies of teaming; AI Assistant, Ad-hoc Dependency, Ad-hoc Forced Dependency, Paired Equanimity, and Group Equanimity. Each cluster represents a unique combination of holistic team-level characteristics, indicating there are multiple disparate team types studied under the same definition. In turn, this raises the question of whether insights are truly transferable between papers. We conclude with guidance on how to identify the types of human-AI teams studied, a checklist for reporting a human-AI team in research work, and ways in which the field can be further synthesised.

Problem

• Human-AI teaming
• team types
• taxonomy
• research comparability
• team classification

Innovation

• human-AI teaming
• team taxonomy
• psychological classification
• research synthesis
• collaborative AI