The Effect of Anthropomorphic Design on Information Trust and Adoption Intention in AI Chatbots

DOI

10.2991/978-2-38476-609-3_50How to use a DOI?

Keywords

Anthropomorphic Design; Information Trust; Adoption Intention; SOR Model; TAM Model

Abstract

This study examines how human-like AI chatbots affect users’ trust in their information and willingness to follow their advice. The study puts together the Stimulus-Organism-Response (SOR) model and the Technology Acceptance Model (TAM). These models help show two things: how helpful users find the AI, and how easy they find it to use, and how a person's own tendency to see things as human works as a moderator. The authors ran an experiment with two factors. One factor was how the AI talked—like a person or in a neutral way. The other factor was what the task was about—finding facts or dealing with emotions. A total of 189 participants with prior AI chatbot experience took part. The results show that the immediate effect of anthropomorphic focus on information trust was insignificant. However, trust strongly predicted adoption intention. Perceived usefulness served as a significant mediator, but the effect was negative—making the AI sound more human actually reduced users’ perception of its functional value. Whether users found the AI easy to use did not bridge the link. The effect of their human-like view was only small. These findings suggest that adding human-like features does not automatically build user trust. Designers should apply anthropomorphic design with care, considering the task type. For information-seeking tasks, a more neutral style may be effective. For emotional support scenarios, a warmer tone may be helpful. A thoughtful approach that considers both the task and the user is likely to work better.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yiyang Bai
AU  - Yichang Guo
AU  - Jialei Yu
PY  - 2026
DA  - 2026/09/04
TI  - The Effect of Anthropomorphic Design on Information Trust and Adoption Intention in AI Chatbots
BT  - Proceedings of the 2026 3rd International Conference on Public Relations and Media Communication (PRMC 2026)
PB  - Atlantis Press
SP  - 458
EP  - 473
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-609-3_50
DO  - 10.2991/978-2-38476-609-3_50
ID  - Bai2026
ER  -