The integration of Artificial Intelligence (AI) necessitates determining whether systems function as tools or collaborative teammates. In this study, by synthesizing Human-AI Interaction (HAI) literature, we analyze this distinction across four dimensions: interaction design, trust calibration, collaborative frameworks and healthcare applications. Our analysis reveals that static interfaces and miscalibrated trust limit AI efficacy. Performance hinges on aligning transparency with cognitive workflows, yet a fluency trap often inflates trust without improving decision-making. Consequently, an overemphasis on explainability leaves systems largely passive. Our findings show that current AI systems remain largely passive due to an overreliance on explainability-centric designs and that transitioning AI to an active teammate requires adaptive, context-aware interactions that support shared mental models and the dynamic negotiation of authority between humans and AI.
@article{arxiv.2602.15865,
title = {AI as Teammate or Tool? A Review of Human-AI Interaction in Decision Support},
author = {Most. Sharmin Sultana Samu and Nafisa Khan and Kazi Toufique Elahi and Tasnuva Binte Rahman and Md. Rakibul Islam and Farig Sadeque},
journal= {arXiv preprint arXiv:2602.15865},
year = {2026}
}