KVKK for AI Agents · concept · an Avalanche AI example wiki verified 2026-07-23 · live

Employee Use of Generative AI Tools — a Different Problem Than Deploying One

Generative AI Guide (15 Soruda) — What KVKK Actually Said and Etken Yapay Zekâ (Agentic AI) Guidance — KVKK's March 2026 Framework both assume an organization that deliberately built or deployed an AI system. Most KOBİs have a more immediate exposure: employees already pasting customer data, contracts, and internal documents into consumer AI tools on their own initiative, with no processing agreement, no role assignment, and no one who decided this was a processing activity at all. KVKK's guidance on workplace generative-AI use targets exactly this gap.

Why this is a distinct problem, architecturally

Everything in Deployment Patterns — KVKK-Aware Agent Architecture assumes you control the system — what enters its context, where transcripts live, who the processor is. None of that applies when the "system" is an employee's personal ChatGPT account. The controls are organizational and behavioral before they are technical:

The practical order of operations for a KOBİ

1. Find out what's already happening — ask, don't assume. Shadow use is the default state, not an edge case. 2. Classify the data categories that matter (customer PII, employee data, special categories, trade secrets — KVKK only governs the personal-data slice, but the business risk is broader). 3. Write the policy, scoped to what you found in step 1, not a generic template. 4. Pick (or formally bless) a small number of business-tier tools, assign controller/processor roles in writing, and route this into the same decision trail as any deliberately deployed agent (Pattern 5).

Where this fits in the reading order

If you are advising a KOBİ that has not yet built or bought an AI agent, this page is where the conversation actually starts — before Deployment Patterns — KVKK-Aware Agent Architecture, not after.

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Educational reference maintained by Avalanche AI — not legal advice.