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When Your Chatbot Makes a Promise: AI Customer Agents and Consumer Law in Türkiye and the EU

Your support chatbot just told a customer the subscription is refundable within 60 days. Your terms say 14. Who is bound? For companies selling to consumers in Türkiye and the EU, the answer is uncomfortable: probably you. AI customer-facing agents create consumer-law exposure that most teams have not priced, because the chatbot sits in marketing’s budget and the liability lives in legal’s.

The binding-statement problem

Under Turkish consumer law (TKHK) and its e-commerce framework, pre-contractual information and representations made in the seller’s channels bind the seller. A chatbot on your domain, speaking in your brand voice, is your channel. Courts and consumer arbitration boards will not parse whether the promise came from a human agent or a language model; the question is whether a reasonable consumer relied on it. Hallucinated discounts, invented return windows and confident misstatements of product capabilities are, functionally, your statements.

Layered duties, one interface

  1. TKHK + e-commerce law (now): accurate pre-contractual information, no misleading commercial practice, order-confirmation duties; all indifferent to whether AI generated the text.
  2. KVKK (now): the conversation is personal data processing; aydınlatma at the chat entry point, retention limits on transcripts, and care with what the bot solicits (“share your ID number to continue” is a design decision with legal weight).
  3. AI Act Article 50 (from 2 August 2026, EU-facing): the consumer must know they are talking to a machine, where not obvious. The “obvious” carve-out is narrower than product teams assume; a bot named “Elif” with a human avatar is engineered ambiguity.
  4. ETBİS layer: if you operate e-commerce in Türkiye, your registered service descriptions should not diverge from what your bot promises (see our ETBİS guide).

Design the safety rails, not just the prompt

  • Authority limits: decide what the bot may commit to (nothing financial beyond published terms is a sane default) and enforce it in the orchestration layer, not merely in the system prompt.
  • Grounding over generation for anything with legal content (refunds, warranties, pricing) retrieve from the canonical policy, do not let the model improvise.
  • Human hand-off triggers for complaints, vulnerable users, and any conversation drifting into dispute territory.
  • Transcript retention matched to your dispute window: the transcript is your best evidence and your KVKK liability at once; set a schedule instead of keeping everything forever.
  • Correction protocol: when the bot misstates, an addressable process (honour, correct, notify) turns a pattern into an incident instead of a class of claims.

The quiet upside

A well-railed bot is also a compliance asset: it delivers mandatory information consistently, timestamps disclosures, and never gets tired on aydınlatma. The gap between an exposure and an asset is entirely in the engineering around the model.

For the contract layer between you and your bot vendor, the six clauses in our GPAI piece apply squarely here.

This article is for general information only and does not constitute legal advice. It reflects the position as of July 2026.

Author

  • Erdem Mümtaz Hacıpaşaoğlu

    Mümtaz is the Managing Partner of Vircon Legal, which he founded in 2016. He advises founders, investors and operators on financing rounds, M&A, cross-border incorporations and regulated verticals such as crypto-asset infrastructure, fintech and games, bringing a former startup founder's perspective to every engagement.

    View all posts
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Published: 20 July 2026 · last updated: 10 August 2026
This article is for general informational purposes only and does not constitute legal advice. Laws and practices may have changed since the publication date. For specific situations, please consult Vircon Legal.
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