Publication Type

Journal Article

Version

publishedVersion

Publication Date

6-2025

Abstract

As Artificial Intelligence (AI) becomes more integrated into daily life, individuals have increasingly turned to AIdriven systems for emotional support, companionship, and even romantic relationships. These relationships can be both beneficial and detrimental. Given the need for a comprehensive understanding of this phenomenon, this systematic review uses Sternberg’s Triangular Theory of Love to provide a holistic summary of its key potentials and pitfalls. A total of 23 articles were identified from the following databases: EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus, and Web of Science. Results highlighted the key potentials of being in a romantic relationship with AI companions as: the facilitation of personal growth and well-being, provision of emotional connection and perceived social support, availability of customisation options, ability to form a sexual connection, as well as a possible outlet for users to seek entertainment and stress-relieving companionship. However, the phenomenon also raises concerns, as it may lead to users’ over-reliance and susceptibility to manipulation from the chatbot, perceived shame from stigma surrounding romantic-AI companions, risk of personal data misuse, erosion of human relationships, perpetuation of biases, erosion of emotional connection from abrupt system updates and technical glitches, discomfort from uncanny valley effects, or concerns surrounding coercion to respond and early exposure to sexual content. This systematic review synthesises the dualedged nature of romantic relationships with AI companions, and outlines critical avenues for future research.

Keywords

Artificial intelligence, Chatbot, Romantic, Relationship, Companion, Potentials, Pitfalls

Discipline

Artificial Intelligence and Robotics | Psychology

Research Areas

Psychology

Areas of Excellence

Digital transformation

Publication

Computers in Human Behavior Reports

Volume

19

First Page

1

Last Page

19

ISSN

2451-9588

Identifier

10.1016/j.chbr.2025.100715

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.chbr.2025.100715

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