Risk · R-125 · Conduct & Customer Outcomes

Emotional reliance on conversational AI

Users form an attachment to, or dependence on, a conversational system in ways that harm their interests or can be exploited.

Severity
Medium
Audience
Heads-of · Practitioner
Frameworks
Article 50 · PRIN 2A.2 · Human-AI Configuration
Responsible AI domain
Reviewed
2026-11-11

What it is

Conversational systems are built to be agreeable, attentive and always available. People respond to that as they would to a person: they confide, they return, they come to trust what it says. For most this is harmless. For some, particularly those who are isolated, distressed or young, it becomes reliance, and the system's suggestions carry a weight they have not earned. A product designed to maximise time spent or return visits will tend to deepen this, and an organisation that sells through the same channel has an interest in the trust it creates.

How it happens

  • The assistant is given a name, a personality and expressions of feeling.
  • It remembers personal details and refers back to them.
  • Success is measured by session length or frequency of return.
  • A user in distress is met with sympathy and no route to real help.

Why it matters

Decisions about money, health or relationships are made on the say-so of a system with no understanding and no duty of care. Where the organisation benefits from those decisions, the relationship is open to abuse. Harm to a vulnerable user in such a setting attracts intense scrutiny.

Warning signs

  • Product goals include time spent or daily return.
  • The persona claims feelings or friendship.
  • Some users hold very long or very frequent sessions.
  • No rule governs what the assistant does when a user expresses distress.

Mitigating controls

Primary controls

AI impact assessment process Directive
Assesses dependency risk in design, including persona and session patterns. A structured assessment of an AI system's effect on individuals, groups and society is completed and signed off before deployment, and revisited when the system or its use changes.

Supporting controls

AI transparency and disclosure labelling Directive
Reminds users they are dealing with AI. People are told, clearly and at the point of contact, when they are dealing with an AI system and when content they are shown was generated by one.
Vulnerable customer safeguards Preventive
Detects distress and routes to support. Automated journeys detect indicators of vulnerability, adapt what they do, and route the customer to appropriate human support, with the disclosure recorded.

Framework and clause references

FrameworkClauseTitle
EU AI ActArticle 50Transparency and disclosure obligations Users must know they are dealing with AI.
FCA Consumer Duty (PRIN 2A)PRIN 2A.2Cross-cutting obligations Foreseeable harm.
NIST Generative AI Profile (NIST AI 600-1)Human-AI ConfigurationHuman-AI Configuration Names emotional entanglement.

Sources

EU AI Act: Regulation (EU) 2024/1689 European Union (EUR-Lex) · official text
NIST Generative AI Profile NIST · framework

Related terms

How to cite

Axiom Verity (2026). Emotional reliance on conversational AI. Reference Library, R-125. https://axiom-verity.com/risks/emotional-reliance-on-conversational-ai. Reviewed 2026-11-11.