From Friends to Lovers: Understanding Motivations and Barriers in AI Companionship

Artificial intelligence (AI) companions are increasingly used for social, emotional, and sometimes romantic fulfillment, raising questions about how people perceive and engage with these technologies. This study explored attitudes toward AI companionship and whether interviewer type (AI, human, or unmoderated) affects disclosure or engagement. A mixed-methods design was employed with 135 adult participants, who completed structured interviews including Likert scale items and open-ended questions about their views on AI companions. Most participants (55.6%) expressed hesitancy or resistance toward emotionally significant relationships with AI, although several reported openness to non-intimate or functional companionship such as friendship or mentoring. Motivations for engaging with AI included its non-judgment and trustworthiness, as well as its ability to provide emotional support and optimize daily life. Key barriers involved its lack of physicality, lack of humanity, incapacity to form an emotional connection, and privacy concerns. Participants in the unmoderated condition rated AI as a friend significantly higher than those in the human interviewer condition, and rated AI as equivalent to a human companion and as a potential romantic partner significantly higher than those in both the chatbot and human interviewer conditions. No statistically significant differences emerged across conditions in self-reported honesty. Participants' engagement metrics were generally higher in the human and unmoderated interviews compared to AI. These findings offer methodological insights for research on sensitive topics and highlight the complex, context-dependent ways people relate to AI companionship. Implications for policy, clinical practice, and the design of future AI companion systems are discussed.

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Publication Details

Journal
Archives of Sexual Behavior
Published
2026-06-24
DOI
https://doi.org/10.1007/s10508-025-03375-0
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

From Friends to Lovers: Understanding Motivations and Barriers in AI Companionship

Simon Dubé, Valérie Lapointe, Laura M. Vowels, Shannon K. Sweeney et al.
Archives of Sexual Behavior
Artificial Intelligence in Healthcare and Education
article

From Friends to Lovers: Understanding Motivations and Barriers in AI Companionship

Simon Dubé, Valérie Lapointe, Laura M. Vowels, Shannon K. Sweeney, Matthew J. Vowels, George Nash, Temian Schnell
article en

Abstract

Artificial intelligence (AI) companions are increasingly used for social, emotional, and sometimes romantic fulfillment, raising questions about how people perceive and engage with these technologies. This study explored attitudes toward AI companionship and whether interviewer type (AI, human, or unmoderated) affects disclosure or engagement. A mixed-methods design was employed with 135 adult participants, who completed structured interviews including Likert scale items and open-ended questions about their views on AI companions. Most participants (55.6%) expressed hesitancy or resistance toward emotionally significant relationships with AI, although several reported openness to non-intimate or functional companionship such as friendship or mentoring. Motivations for engaging with AI included its non-judgment and trustworthiness, as well as its ability to provide emotional support and optimize daily life. Key barriers involved its lack of physicality, lack of humanity, incapacity to form an emotional connection, and privacy concerns. Participants in the unmoderated condition rated AI as a friend significantly higher than those in the human interviewer condition, and rated AI as equivalent to a human companion and as a potential romantic partner significantly higher than those in both the chatbot and human interviewer conditions. No statistically significant differences emerged across conditions in self-reported honesty. Participants' engagement metrics were generally higher in the human and unmoderated interviews compared to AI. These findings offer methodological insights for research on sensitive topics and highlight the complex, context-dependent ways people relate to AI companionship. Implications for policy, clinical practice, and the design of future AI companion systems are discussed.

Archives of Sexual Behavior
Université du Québec à Montréal (CA), Indiana University Bloomington (US), The Sense Innovation and Research Center (CH), University of Roehampton (GB), University of Lausanne (CH)
University of Roehampton
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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