Turkish AI Law : A Practical Legal & Compliance Guide for Businesses
Artificial intelligence is no longer an “innovation project” that sits inside an IT department. In Turkey, AI is increasingly used in banking and fintech, e-commerce and retail, HR and recruitment, health and life sciences, call centers, logistics, security, advertising, and content production. As adoption accelerates, legal exposure grows in parallel: privacy complaints, cybersecurity incidents, consumer disputes, unfair competition allegations, IP conflicts, reputational crises from hallucinations or deepfakes, and—most importantly—regulatory scrutiny.
Turkey does not yet have a single, comprehensive “AI Act” equivalent to the EU’s regime. But that does not mean AI is unregulated. On the contrary: the Turkish legal system already contains strong, enforceable rules that apply to AI through data protection (KVKK), civil liability, consumer protection, sectoral regulations, IP law, and cybersecurity rules. At the same time, Turkey’s policy documents and parliamentary proposals show a clear direction: risk management, transparency, accountability, and special attention to AI-generated content and public safety.
This article explains the current legal reality for AI in Turkey and offers a practical compliance roadmap that businesses can implement now—whether you build AI systems, deploy third-party tools, or use generative AI to create content and automate workflows.
Important note: This text is for general information and does not constitute legal advice. AI projects are highly fact-specific; compliance strategy should be tailored to your data, sector, and risk profile.
1) The Regulatory Landscape: “No Single AI Law” Does Not Mean “No AI Rules”
1.1. Turkey’s policy direction: AI strategy and action plans
Turkey has treated AI as a strategic technology in national planning. The National Artificial Intelligence Strategy (2021–2025) and later implementation planning emphasize capacity building, governance, and sectoral adoption.
In addition, Turkey’s development planning frames AI as a pillar for competitiveness and digital transformation.
These documents are not “laws,” but they matter for businesses because they signal:
- increasing public investment and public-sector use of AI,
- greater regulatory interest in AI governance,
- and a likely alignment trend with global standards (especially for international trade and cross-border data flows).
1.2. Parliamentary proposals: a clearer signal of what may come next
Two developments are especially relevant for 2026:
- A comprehensive AI Law Proposal submitted to Türkiye Büyük Millet Meclisi in June 2024 (TBMM document no. 2/2234). It describes AI principles (e.g., security, transparency, fairness, accountability, privacy), a risk-based approach, compliance duties for “operators,” oversight powers, and significant administrative fines in the proposal text.
- A separate November 2025 draft focusing on AI-generated content / deepfakes, proposing amendments across multiple laws (including internet-content regulation, criminal law elements, data protection concepts, and telecom/cybersecurity measures). This draft includes a definition of “AI system” and proposes fast content takedown / access blocking mechanisms for certain AI-generated content categories, as well as penalties and shared responsibility concepts for some actors.
Practical takeaway: even if these texts are not yet enacted, they are strong compliance signals. Businesses should already be building documentation, controls, and governance consistent with these themes—because retrofitting later is far more expensive.
1.3. The EU AI Act effect: why Turkey-based companies should care
Many Turkey-based companies operate in the EU market, work with EU customers, or use EU-based vendors. The EU’s AI Act creates a compliance gravity that often reaches beyond EU borders through supply chains and contractual requirements. The European Commission explains the AI Act’s phased implementation and risk-based obligations, and official EU materials emphasize strong controls for high-risk AI and transparency duties for certain AI systems.
Practical takeaway: If you sell to the EU, process EU residents’ data, or provide AI-enabled services to EU clients, you should expect AI governance requests in procurement, audits, and contractual clauses—even if Turkey’s local AI law remains under development.
2) The Core Enforceable Rule Today: Data Protection (KVKK) and AI
The single most immediate legal constraint for AI in Turkey is data protection. AI projects often rely on personal data (customer behavior, call recordings, chat logs, biometrics, employee performance, device identifiers, location data, etc.). Under Turkish law, AI-based personal data processing must comply with Law No. 6698, enforced by the Kişisel Verileri Koruma Kurumu.
2.1. Automated decision-making: a key right you cannot ignore
A crucial KVKK point for AI systems is the individual’s right to object to outcomes against them resulting from analysis conducted solely by automated systems (Article 11). This matters directly for:
- credit scoring and loan approvals,
- fraud detection blocks,
- recruitment filtering and ranking,
- dynamic pricing,
- insurance risk scoring,
- account suspensions or content moderation decisions based purely on automated tools.
Compliance implication: If your AI produces decisions with legal or significant effects, you should build:
- meaningful human review (where feasible),
- explanation capability (at least at a functional level),
- and a complaint-handling path that can reverse or correct outcomes.
2.2. Special categories and biometrics: high-risk territory
KVKK treats certain data as “special categories” (including biometric and health data). AI frequently touches these categories in facial recognition, voiceprints, emotion analysis, medical imaging tools, and workplace security solutions. KVKK’s law text and guidance emphasize strict conditions and safeguards for such processing.
Practical approach: If your AI project uses biometric data (face/voice), treat it as a high-risk project: restrict scope, justify necessity, implement strong access controls, log usage, and prepare a robust legal basis and disclosure strategy.
2.3. Generative AI and KVKK: new guidance you should track
KVKK has published dedicated guidance on generative AI and personal data protection (“15 questions” format), intended to help data controllers evaluate generative AI use cases and lifecycle processing.
Even without quoting it, the direction is consistent with global best practices:
- clarify roles (controller vs. processor) in AI tool usage,
- define lawful basis for input data and any reused logs,
- manage cross-border transfers carefully,
- prevent unnecessary disclosure of personal data into prompts,
- and maintain transparency and data subject rights workflows.
2.4. Cross-border data transfers: critical for cloud AI and global vendors
Most AI tools involve cloud infrastructure and international vendors. Turkey reformed parts of cross-border transfer rules and developed supporting instruments such as standard contractual safeguards and transfer-related guidance published on KVKK’s channels.
Compliance implication: If you send personal data to an AI vendor abroad (or the vendor’s sub-processors abroad), your contract structure must reflect KVKK’s cross-border requirements. As a baseline, you should have:
- a clear data-processing agreement,
- explicit allocation of roles,
- transfer safeguards (where applicable),
- and documented decisions about which data can be sent to the tool.
3) Cybersecurity and AI: Security Obligations Are Expanding
AI increases cybersecurity risk in two ways:
- AI systems process large volumes of data and often integrate with core systems; a breach can be wider and more damaging.
- AI can be abused (prompt injection, data exfiltration via model behavior, model inversion, deepfake fraud, automated phishing, etc.).
Turkey’s Cybersecurity Law No. 7545 (published 2025) reflects a stronger, more centralized cybersecurity policy approach, including governance structures and protective principles in cyberspace.
Practical takeaway: AI governance must include cybersecurity governance. For many companies, that means:
- pre-deployment security testing (including vendor security due diligence),
- least-privilege access to prompts and logs,
- segmentation (don’t let a chatbot touch everything),
- incident response playbooks that include AI-specific threats,
- and audit-ready logs for critical AI-enabled processes.
For guidance and internal governance, recent technical policy materials (e.g., TÜBİTAK guidance on responsible generative AI use) can also support compliance-by-design programs—even when not legally binding.
4) AI-Generated Content, Deepfakes, and Online Platform Risk
Businesses increasingly use generative AI for marketing assets, product images, voiceovers, customer communications, and internal content creation. Legal exposure arises from:
- defamation and reputational harm,
- infringement of personality rights,
- misleading advertising,
- consumer deception,
- election/public order risks,
- and fraud via impersonation deepfakes.
Turkey already has an online content regulation framework (e.g., Law No. 5651).
In addition, the November 2025 parliamentary draft proposes a specialized response to certain AI-generated content risks—introducing a statutory definition of AI systems and a fast response approach (access blocking / removal deadlines), plus enforcement tools and penalties in specific contexts.
Practical takeaway (even before any new law):
- Build a deepfake response protocol (detection, evidence preservation, takedown requests, platform notices, and legal escalation).
- Establish a content provenance workflow for brand assets (approval trail, source documentation, and “human review before publication”).
- Require AI content labeling internally (and publicly where appropriate) to reduce deception risk.
5) Civil Liability: When AI Causes Damage, Who Pays?
Even without a dedicated AI statute, Turkish civil law can impose liability through:
- fault-based tort principles (negligence),
- contractual liability (failure to meet promised performance),
- and product/service safety concepts (especially in consumer contexts).
AI systems fail in predictable ways: bias, hallucination, wrong classification, inaccurate scoring, faulty automation, or security vulnerabilities. Liability analysis typically focuses on:
- duty of care (what precautions were expected?),
- foreseeability of harm,
- adequacy of human oversight,
- documentation (policies, testing, logs),
- and whether the risk was properly disclosed and contractually allocated.
Risk hotspot examples:
- A recruitment tool unlawfully discriminates or filters candidates with no meaningful review.
- A credit scoring model produces systematic errors and blocks customers unfairly.
- A medical triage or decision-support tool misguides users.
- A customer support chatbot gives incorrect legal/financial guidance and causes measurable harm.
- A generative AI marketing campaign produces infringing or defamatory content.
Practical compliance: Courts and regulators are more sympathetic to companies that can prove “reasonable governance”: testing, validation, monitoring, and correction mechanisms.
6) Intellectual Property: Training Data, Outputs, Trade Secrets, and Branding
AI creates a complex IP landscape. Turkey’s IP and copyright framework will matter in at least four areas:
- Training data and datasets: Do you have rights to use the materials? Are there license restrictions? Are you using proprietary datasets or scraping?
- Outputs: Who owns AI-generated materials in contracts? Is the output sufficiently original? Does it incorporate protected elements?
- Trade secrets and confidentiality: Prompts, product roadmaps, and internal documents can leak into vendor logs if controls are weak.
- Brand and advertising: AI can generate confusingly similar branding, slogans, or visuals that trigger unfair competition and trademark disputes.
Practical contracting tip: IP risk is often best managed contractually through:
- output ownership clauses,
- warranties about training rights (where available),
- indemnities for infringement,
- and strict confidentiality / data-use limitations.
7) Sector-Specific Compliance: The Rules Multiply in Regulated Industries
Finance (banking, payments, fintech)
AI use in finance typically triggers layered obligations: consumer fairness, transparency, AML/fraud controls, and sometimes model governance expectations through sector regulators. If your scoring affects individuals materially, KVKK automated decision rights and complaint channels become especially important.
Health and life sciences
Health data and medical decision support are high-risk. Medical claims, patient privacy, and safety validation must be handled with extreme care. If AI influences diagnosis or treatment decisions, documentation and oversight are essential.
Telecom, platforms, and online services
If your service is a platform, AI content moderation and recommendation systems can create both data protection and public-policy risks—especially in deepfake scenarios and fast response obligations under content regulation discussions.
8) A Practical AI Compliance Roadmap for Turkey-Based Businesses
Below is a roadmap you can implement immediately—without waiting for a comprehensive AI law.
Step 1: Map your AI use cases and classify risk
Create a register of:
- purpose and business owner,
- data sources,
- whether decisions affect individuals materially,
- whether special category data is involved,
- and whether output is published externally.
Step 2: Confirm your KVKK legal basis and transparency model
For each use case:
- identify lawful basis under KVKK,
- update privacy notices and internal disclosures,
- define retention (don’t store prompts/logs forever),
- and prepare a data subject request workflow (including automated decision objections).
Step 3: Vendor governance and cross-border transfer readiness
If you use third-party AI:
- sign a processing agreement,
- evaluate where data flows geographically,
- implement cross-border safeguards (where needed),
- and keep documentation for audits.
Step 4: Build human oversight where outcomes matter
Where AI decides, ranks, scores, blocks, or profiles:
- ensure meaningful review capability,
- document escalation and correction,
- and test for discriminatory outcomes and systematic errors.
Step 5: Security controls tailored to AI threats
Minimum controls:
- role-based access to AI tools,
- prompt filtering for personal/sensitive data,
- logging and anomaly detection,
- red-teaming for prompt injection,
- incident response procedures for model-related events.
Step 6: Content governance (generative AI)
- prohibit uploading personal data into public tools unless authorized,
- require human review for public-facing content,
- keep a provenance trail for published materials,
- and prepare a deepfake crisis plan.
Step 7: Document everything
If a regulator or court asks “What did you do to prevent harm?”, your strongest defense is evidence:
- policies, training records, vendor due diligence,
- test results, bias checks, monitoring logs,
- incident reports and corrective action records.
9) Frequently Asked Questions
Q1) Is AI legal in Turkey?
Yes. AI is widely used, but it must comply with existing Turkish laws—especially KVKK (personal data protection), cybersecurity duties, consumer law, and IP rules.
Q2) Does Turkey have an “AI Act” today?
Not in a single consolidated statute. However, a comprehensive AI law proposal has been submitted to TBMM, and another proposal targets AI-generated content and deepfakes.
Q3) Can we use AI for hiring and recruitment in Turkey?
You can, but it is high-risk. You should ensure transparency, proportional data use, and a pathway for human review—especially because KVKK gives individuals the right to object to adverse outcomes produced solely by automated processing.
Q4) Can we send personal data to an overseas AI vendor?
Possibly, but cross-border transfer rules apply. You need appropriate safeguards and contractual structures aligned with KVKK’s transfer framework.
Q5) Are deepfakes and AI-generated impersonations regulated?
Turkey has general legal tools (personality rights, content regulation, criminal law concepts in relevant cases). In addition, a parliamentary draft explicitly addresses certain AI-generated content risks and fast content removal/access blocking concepts.
Q6) Do we need to disclose that we use AI?
There is no single universal disclosure rule for every scenario, but transparency is a core expectation under KVKK and emerging AI governance trends—especially where AI affects individuals or handles personal data.
Q7) What is the biggest legal risk for AI projects in Turkey right now?
In practice: KVKK compliance failures (lawful basis, transparency, special categories, security, cross-border transfers) and reputational harm from AI-generated content incidents.
Q8) How should a company prepare for future AI legislation in Turkey?
Adopt a governance model now: risk classification, documentation, transparency, oversight, security, and vendor controls—consistent with the direction of the AI law proposal and international frameworks.
Conclusion: “AI Compliance” Is a Business Advantage
In Turkey, AI compliance is not just about avoiding fines. It protects brand trust, reduces litigation risk, improves procurement readiness (especially with EU-linked supply chains), and helps scale AI use safely. The companies that win with AI will be the ones that can show, with documentation, that they built systems that are lawful, secure, explainable where it matters, and accountable—aligned with KVKK today and prepared for the likely direction of Turkish AI legislation tomorrow.
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