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10/06/2026 10:36 pm
TL;DR: AI-generated content is making online dating harder to trust, with 84% of UK daters reporting increased scepticism, 54% open to AI-edited profile images, and 28% lacking confidence in spotting deepfakes, according to Sumsub’s survey. The governance problem is no longer just fraud detection but identity verification in a channel where synthetic content is now normalised.
NHIMG editorial — based on content published by Sumsub: AI-generated content is making online dating harder and less trustworthy
By the numbers:
- 84% of UK daters say AI has made online dating harder and less trustworthy.
- More than a quarter of users (28%) say they are not confident in their ability to spot deepfakes or AI-manipulated profiles.
- Over one third (36%) have used an AI companion as an alternative to dating apps.
Questions worth separating out
Q: How should security teams verify identity when AI-generated profiles look authentic?
A: Security teams should stop relying on visual realism or message quality as proof of identity.
Q: Why do AI-generated messages and images weaken trust in digital identity flows?
A: They weaken trust because they remove the reliability of cues people traditionally use to judge authenticity.
Q: What breaks when identity checks depend on human judgement in AI-heavy channels?
A: Human judgement becomes inconsistent once synthetic content is personalised and widely available.
Practitioner guidance
- Separate authenticity checks from content quality signals Do not treat polished text, strong grammar, or realistic images as evidence of a real person.
- Add step-up verification at high-trust moments Trigger stronger checks when users exchange contact details, request payment, or move off-platform.
- Track synthetic-content exposure as an assurance metric Measure how often users encounter AI-generated profiles, messages, or images and correlate that with reporting, abandonment, and verification failure rates.
What's in the full article
Sumsub's full post covers the survey detail this analysis intentionally leaves for the source:
- The UK survey methodology, respondent profile, and fieldwork dates behind the 2,000-person dataset
- Breakdowns of how often users are seeing AI-generated content in dating interactions and what types they report
- The report's fraud and identity-fraud context drawn from Sumsub's 2025 Identity Fraud Report
- The platform-facing governance argument the vendor makes about verification, user awareness, and deepfakes
👉 Read Sumsub's survey findings on AI, trust, and dating app identity risk →
AI in dating apps: is verification keeping up with trust loss?
Explore further
11/06/2026 2:42 am
Synthetic identity is now a governance problem, not just a fraud problem. The article shows that users are not merely encountering more scams, they are adapting to an environment where authenticity itself is being industrialised. That changes the governance question from “how do we block bad actors” to “how do we prove identity when the medium is synthetic by default.” Practitioners should treat this as an assurance design issue across digital channels.
A few things that frame the scale:
- The average estimated time to remediate a leaked secret is 27 days, despite 75% of organisations expressing strong confidence in their secrets management capabilities, according to The State of Secrets in AppSec.
- Organisations maintain an average of 6 distinct secrets manager instances, creating fragmentation that undermines centralised control, according to GitGuardian and CyberArk.
A question worth separating out:
Q: Who is accountable when AI-generated identity deception succeeds on a platform?
A: Accountability usually sits with the platform that set the trust model, the verification process, and the abuse response path. If a service allows synthetic identity signals to move users into high-trust interactions without adequate proofing, responsibility is not shifted to the victim. Governance has to cover both design and enforcement.
👉 Read our full editorial: AI-generated dating content is eroding trust and verification
