Qualitative Analysis of Romantic AI Companions

Evidano is an AI-powered qualitative data analysis platform that helps teams turn interviews, chat logs, and survey free text into reproducible themes and cross-segment comparisons.

Romantic AI companions have surged in adoption and raise relationship issues: a Canadian survey (n = 1, 815) reported that approximately 50% view partner use as infidelity, around 75% would react negatively, and about 66% of users hid their use.

• App growth: romantic AI apps grew approximately +700% from 2022–2025, indicating rapid adoption and the need for qualitative insight.
• Survey scale: the Canadian survey included n = 1, 815 adults (collected before July 6, 2026) and highlights segment differences by gender, age cohort, and relationship style.
• Behavior and prevalence: Character.AI activity reached ≈20M monthly active users in 2025 and US data cited suggest at least 1 in 6 adults interacted at least once, so these companions are not niche.
• Research implication: qualitative studies should prioritize disclosure versus secrecy, perceived betrayal, emotional versus sexual diversion, and cross-segment comparisons (Gen Z vs older, cis women vs cis men, monogamous vs non‑monogamous).

The Conversation summary reports preliminary surveys and recent literature showing rapid market expansion, large platform user counts in 2025, and a Canadian survey of n = 1, 815 adults collected before July 6, 2026. The Conversation authors report attitudinal splits by gender, age cohort, relationship style and ideology.

Scope: the post synthesizes survey results and recent academic reports and is not a longitudinal causal study.

• Key variables to capture in qualitative work: disclosure versus secrecy, perceived betrayal, emotional versus sexual diversion, and comparative expectations (AI versus partner).
• Limitations: results are preliminary; self‑report bias and changing product affordances mean findings should be triangulated with interviews and app logs.

This two‑week pilot workflow reproduces a rigorous qualitative analysis from interview transcripts, 1, 815 survey free‑text responses, and optional chat logs.

Two‑week pilot workflow (inputs: interview transcripts, 1, 815 survey free‑text responses, and optional chat logs):

• 1) Ingest: upload transcripts and survey CSVs to Evidano and enable PII redaction and a custom dictionary for relationship and sexual terminology.
• 2) Map variables: tag demographic fields (age cohort, gender identity, relationship style, ideology) for cross‑segment analysis.
• 3) Auto‑code: run AI‑assisted initial coding to extract themes such as disclosure, secrecy, validation, comparison, and sexual exploration.
• 4) Audit & refine: review AI suggestions, merge or split codes, and lock a validated codebook for reproducibility.
• 5) Segment analysis: produce frequency tables and narrative summaries for cis women versus cis men, Gen Z versus older adults, and monogamous versus non‑monogamous participants.
• 6) Visualize & extract quotes: build co‑occurrence networks and export stakeholder snippets showing patterns of concealment and emotional diversion.
• 7) Iterate: run targeted AI‑avatar follow‑ups for ambiguous cases or to probe longitudinal change with participant consent.

Ethical research of intimate digital behaviors requires informed consent, data minimization, and secure handling.

Researchers should use PII redaction, obtain consent for AI‑avatar follow‑ups, and remember these findings are non‑diagnostic and exploratory.

Romantic AI companions change relational expectations and raise questions about secrecy and betrayal.

For UX teams, clinicians, and researchers the priority is structured, segment‑aware qualitative work that distinguishes motive from meaning.

Run the two‑week pilot in Evidano to convert interviews and surveys into reproducible themes, cross‑segment comparisons, and stakeholder‑ready visualizations, or Try Evidano for free to begin your analysis.