AI compliance in Turkey is a proactive legal discipline rather than a one-time regulatory clearance exercise — because the Turkish regulatory framework for AI is not a single statute but an assembly of overlapping obligations drawn from the Personal Data Protection Law (KVKK, Law No. 6698), the Consumer Protection Law (TKHK, Law No. 6502), the Electronic Commerce Law (Law No. 6563), sector-specific regulations from the Banking Regulation and Supervision Agency (BDDK), the Information and Communication Technologies Authority (BTK), and the Turkish Medicines and Medical Devices Agency (TITCK), and Turkey's National Artificial Intelligence Strategy for 2021–2025. A company that deploys an AI system in Turkey without a structured compliance program faces not a single compliance question but a concurrent set of questions from multiple regulatory authorities — each with different jurisdictional scope, different enforcement mechanisms, and different documentation requirements. This guide explains the core components of an effective AI compliance program under Turkish law, organized around the regulatory frameworks that matter most in practice. For the legal liability framework — covering what happens when AI compliance fails and harm results — see the companion resource on legal liability of AI and automation systems in Turkey. Practice may vary by authority and year — verify current regulatory requirements directly before implementing any AI compliance program in Turkey.
KVKK compliance — the foundation of AI data governance
A lawyer in Turkey advising on AI compliance must explain that KVKK (Law No. 6698) is the foundational compliance framework for any AI system that processes personal data — and virtually every commercially deployed AI system in Turkey does, because even AI systems that operate on anonymized data during inference typically processed personal data during training, and the adequacy of the anonymization is itself a KVKK compliance question. KVKK compliance for AI requires more than a privacy policy and a consent click: it requires identifying the legal basis for each processing activity (KVKK Article 5 bases include explicit consent, contract performance, legal obligation, vital interests, public task, and legitimate interest), documenting those bases in a processing register, and confirming that the legal basis matches the actual processing purpose. For AI training specifically — where large datasets of personal data are used to develop model weights — the legal basis analysis must address not just the initial collection but the training use, because data collected for one purpose (service delivery) may not have a valid legal basis for training use without separate analysis. Practice may vary by authority and year — verify current KVKK Board guidance on legal basis requirements for AI training data processing before finalizing any AI training data governance program.
An Istanbul Law Firm advising on VERBIS registration for AI systems must explain that data controllers that process personal data and meet KVKK Board-defined thresholds (based on employee count or annual financial statement size) must register their processing activities with the VERBIS Data Controllers Registry — and this registration obligation applies to AI processing activities in the same way as any other personal data processing. The VERBIS registration must describe each processing activity, its purpose, its legal basis, the categories of data subjects and personal data processed, the retention period, and the categories of recipients to whom the data is transferred. For AI systems, the VERBIS entry must reflect the actual processing — if an AI system processes health data for medical diagnostic purposes, that processing must be registered with the health data category and the corresponding legal basis (KVKK Article 6 special category consent or statutory exception). A VERBIS registration that describes AI processing in generic terms without capturing the specific categories, purposes, and legal bases of the AI's actual data processing does not satisfy the registration obligation and creates regulatory exposure in any KVKK Board inspection. Practice may vary — verify current VERBIS registration requirements for AI-specific processing activities and the specific data category classification applicable to the AI system's inputs before completing any VERBIS registration for an AI deployment.
A law firm in Istanbul advising on privacy impact assessments (PIAs) for AI must explain that while KVKK does not use the term "DPIA" (Data Protection Impact Assessment) explicitly in the way GDPR Article 35 does, KVKK's implementing regulation and KVKK Board guidance indicate that data controllers should conduct privacy impact assessments for high-risk processing activities — and AI systems that make automated decisions with significant consequences for individuals, process special categories of personal data at scale, or involve large-scale profiling are among the highest-risk processing activities that trigger this obligation. A privacy impact assessment for an AI system must evaluate: the necessity and proportionality of the processing; the risks to data subjects (including discrimination from biased outputs, loss of control over personal information, and security risks from data aggregation); the measures in place to mitigate those risks; and the residual risk after mitigation. We conduct PIA exercises for every AI client with significant personal data processing exposure — because a documented PIA is the most important single document for demonstrating compliance good faith in any KVKK Board investigation. Practice may vary — verify current KVKK Board PIA guidance and the specific high-risk processing categories that require PIA before deploying any AI system with significant personal data processing. The KVKK audit defense framework is analyzed in the resource on legal representation in Turkish data protection board investigations.
Automated decision-making — KVKK Article 11 compliance
An English speaking lawyer in Turkey advising on automated decision-making compliance must explain that KVKK Article 11 gives data subjects the right to object to decisions that are produced solely by automated processing and produce significant legal effects or similarly significant consequences — and the KVKK Board has increasingly aligned its guidance with GDPR Article 22 standards, treating automated credit decisions, algorithmic hiring screens, insurance underwriting outputs, and medical diagnostic AI recommendations as significant automated decisions that trigger specific compliance obligations. The compliance obligations for significant automated decisions include: informing data subjects that an automated system is used and how it works in terms they can understand; providing data subjects with the right to request human review of the automated decision; and being able to provide a meaningful explanation of the factors that contributed to the decision when a data subject requests one. A company that deploys a credit scoring AI without informing applicants of the automated nature of the assessment and without providing a mechanism for human review is in violation of KVKK Article 11 obligations regardless of the technical sophistication of the underlying model. Practice may vary by authority and year — verify current KVKK Board guidance on significant automated decision standards and the specific transparency and review mechanisms required before deploying any AI system that makes significant decisions about individuals.
A Turkish Law Firm advising on explainability requirements for AI decisions must explain that the KVKK's transparency obligation — and the data subject's right to request explanation of automated decisions — requires that the company actually be able to produce a meaningful explanation, not merely a technically accurate description of the model's architecture. A post-hoc explanation that describes the model as a "neural network with 12 layers trained on credit bureau data" does not satisfy the transparency obligation for a credit decision — the explanation must be meaningful to the affected individual, which typically requires identifying the specific factors (income level, credit history, debt-to-income ratio) and their relative weights in the decision. For AI systems where explanations are technically complex — such as deep learning models with non-interpretable features — building in explanation mechanisms (LIME, SHAP, or other interpretability tools) at the design stage is significantly less costly than attempting to reverse-engineer explainability after deployment. We advise clients to treat explainability as a design requirement — documented in the AI system's technical specification — rather than as an afterthought that compliance teams must manage post-deployment. Practice may vary — verify current KVKK Board explainability standards and the specific explanation format expected for the AI system's decision type before finalizing any explainability mechanism design.
A lawyer in Turkey advising on the consent framework for AI profiling must explain that KVKK requires explicit consent (açık rıza) for the processing of sensitive personal data categories defined in KVKK Article 6 — including health data, biometric data, genetic data, religious beliefs, political opinions, and trade union membership — and these categories frequently appear in AI training datasets without the data controller having specifically analyzed whether the AI's use of these attributes constitutes processing of sensitive personal data. An AI system trained on medical records to predict disease risk is processing health data (a sensitive category) in the inference phase as well as the training phase — because each inference that predicts a specific individual's health risk involves deriving sensitive personal information from input data. An AI hiring screen that uses language patterns that correlate with political opinions or religious beliefs — even if the model was not explicitly trained with those attributes labeled — may be processing sensitive personal data without explicit consent. We conduct data flow analysis for every AI mandate to identify whether any model inputs, intermediate representations, or outputs involve sensitive personal data categories, before any deployment proceeds. Practice may vary — verify current KVKK Board sensitive data processing standards and the specific consent requirements applicable to the AI system's data categories before finalizing any AI deployment involving potential sensitive data processing. The complete KVKK compliance framework is analyzed in the resource on personal data protection law in Turkey.
Cross-border data transfers and AI cloud infrastructure
An Istanbul Law Firm advising on cross-border data transfers for AI systems must explain that KVKK Article 9 restricts the transfer of personal data outside Turkey to countries that the KVKK Board has determined provide adequate data protection — or to transfers covered by explicit data subject consent, or by standard contractual clauses (SCCs) approved by the KVKK Board. For AI systems hosted in cloud infrastructure outside Turkey — which is the case for the majority of enterprise AI systems using US or EU-based cloud providers — the cross-border data transfer analysis must cover not just the final model output but every stage of the AI pipeline where personal data is processed: data collection and storage, model training (if conducted in cloud infrastructure), model inference (if the inference API is hosted abroad), and model monitoring data (if performance data containing personal data is sent to a foreign monitoring service). The KVKK Board's adequacy list and approved SCC formats are distinct from the GDPR's equivalents, and a transfer mechanism that is valid under GDPR (such as EU SCCs) is not automatically valid under KVKK — Turkish law requires either KVKK Board adequacy determination or a KVKK Board-approved SCC with the specific counterparty. Practice may vary by authority and year — verify current KVKK Board adequacy determinations and the specific approved SCC format required before implementing any cross-border transfer mechanism for AI processing involving Turkish personal data.
A law firm in Istanbul advising on BTK data localization requirements for AI must explain that Turkey's information and communication technology regulatory framework — administered by BTK — includes data localization requirements for certain categories of data that go beyond KVKK's cross-border transfer framework. BTK's secondary legislation requires certain operators (including social network providers above defined user thresholds under Law No. 5651) to store Turkish users' data in Turkey, and this requirement applies to the data processed by AI systems operated by covered entities. For AI systems operated by digital platforms subject to Law No. 5651, the data localization requirement means that training data, inference logs, and user interaction data from Turkish users must be stored on servers located in Turkey — even if the AI model itself is hosted abroad for computational efficiency reasons. A platform that uses a foreign-hosted AI service to process the data of Turkish users must assess whether the data processed through that service falls within the Law No. 5651 localization requirement and whether the AI service's architecture can accommodate localization constraints. Practice may vary — verify current BTK data localization requirements and the specific AI processing activities that fall within Law No. 5651's scope before designing any AI cloud architecture for a digital platform with Turkish users.
An English speaking lawyer in Turkey advising on vendor contract compliance for AI supply chains must explain that a company that uses a third-party AI service provider to process personal data is a data controller that has engaged a data processor — and KVKK requires that the data processing relationship be governed by a data processing agreement (işleme sözleşmesi) that meets KVKK's requirements for controller-processor arrangements. The KVKK data processing agreement must define: the scope of processing authorized by the controller; the technical and organizational security measures the processor must implement; the processor's obligation to process only on documented instructions; the processor's obligation to notify the controller of any security incident affecting the processed data; and the processor's obligations regarding sub-processors. For AI systems, the controller-processor agreement must specifically address the AI-specific processing activities — training data access, model update procedures, inference logging, and the use of aggregated outputs for model improvement — because standard IT vendor agreements are typically not drafted with the specific AI processing workflow in mind. Practice may vary — verify current KVKK controller-processor agreement requirements and the specific AI-specific clauses that KVKK Board guidance expects before finalizing any AI vendor contract for a system that processes Turkish personal data. The GDPR and KVKK alignment framework is analyzed in the resource on GDPR and KVKK compliance for international companies in Turkey.
Algorithmic transparency and bias mitigation programs
A Turkish Law Firm advising on algorithmic transparency compliance must explain that Turkey's KVKK framework — combined with sector-specific regulatory guidance from BDDK, SPK, and TITCK — creates a de facto algorithmic transparency obligation for AI systems that make significant decisions in financial services, healthcare, and employment, even though Turkey does not yet have a horizontal AI transparency statute equivalent to the EU AI Act. The algorithmic transparency obligation in practice means: documenting the decision logic of the AI system in terms that the relevant regulator can assess (not merely technical model documentation, but regulatory-facing explanations of what factors drive decisions and how); maintaining records of the AI system's performance metrics (accuracy, false positive/negative rates, and demographic performance breakdowns) at defined intervals; and being able to demonstrate to the KVKK Board or the relevant sector regulator that the AI system operates as disclosed when responding to a regulatory inquiry or a data subject's challenge. We develop regulatory-facing AI transparency documentation as a standard component of every AI compliance program — structured to address both the KVKK Board's data protection focus and the relevant sector regulator's domain-specific questions. Practice may vary — verify current sector-specific algorithmic transparency requirements and the specific documentation format expected by the relevant regulator before finalizing any AI transparency documentation for a regulated sector deployment.
An Istanbul Law Firm advising on bias audit requirements must explain that while Turkish law does not yet impose a statutory bias audit requirement on AI systems equivalent to the EU AI Act's conformity assessment for high-risk AI, several regulatory frameworks create bias-adjacent obligations that have the practical effect of requiring bias analysis. Under KVKK, the use of personal data to make decisions that produce discriminatory outcomes — even unintentionally through proxy variables — implicates the proportionality and fairness principles that the KVKK Board applies in assessing processing legitimacy. Under TKHK, AI-driven discrimination in consumer service delivery can constitute an unfair commercial practice. Under the Labor Code framework, AI hiring tools that produce discriminatory outcomes can create employer liability for discriminatory employment practices. A bias audit — systematically testing whether the AI system produces materially different outcomes for different demographic groups that are not justified by the decision's legitimate criteria — provides the empirical foundation for demonstrating that these obligations are met. We conduct or coordinate bias audits for AI mandates in employment, credit, insurance, and consumer service contexts as a proactive compliance measure. Practice may vary — verify current regulatory bias assessment expectations applicable to the specific AI deployment context before designing any bias audit program.
A lawyer in Turkey advising on AI performance monitoring programs must explain that a compliance program that validates an AI system at the time of deployment and then does not systematically monitor its performance during the operational period is inadequate — because AI systems can experience model drift (declining accuracy as the real-world distribution of inputs diverges from the training distribution), concept drift (the relationship between inputs and correct outputs changes over time), and adversarial degradation (the model's performance deteriorates due to deliberate manipulation of inputs). A model that was compliant at deployment may become non-compliant over time as its performance degrades, and without systematic monitoring, the compliance gap may not be detected until after harm has occurred. Effective AI performance monitoring programs define specific performance metrics, establish baseline benchmarks at deployment, set threshold triggers that require investigation or remediation when performance falls below defined levels, and assign responsibility for monitoring to specific individuals within the organization. We design AI performance monitoring programs that integrate with existing quality management and compliance systems — ensuring that the monitoring triggers connect to documented remediation workflows rather than remaining isolated technical metrics. Practice may vary — verify current regulatory performance monitoring expectations for the specific AI system type and sector before designing any AI performance monitoring program.
Sector-specific compliance programs — BDDK, TITCK, and BTK
An English speaking lawyer in Turkey advising on BDDK AI compliance for financial institutions must explain that the Banking Regulation and Supervision Agency (BDDK) has developed an increasingly detailed regulatory framework for AI and algorithmic systems in Turkish banking, insurance, and financial services — built through its information security regulation, operational risk guidance, and outsourcing regulation rather than through a dedicated AI statute. The key BDDK requirements for AI compliance in financial services include: maintaining a model inventory documenting all AI and algorithmic models in production with their intended use, data inputs, and performance metrics; conducting model validation before deployment (including back-testing on historical data and stress-testing against adverse scenarios); maintaining model governance documentation showing who approved the model, on what basis, and with what risk controls; and establishing model risk management procedures for identifying and addressing model performance degradation. For foreign fintech companies providing AI services to Turkish banks as B2B vendors, BDDK's outsourcing regulation effectively extends these requirements to the vendor through the bank's due diligence and audit right obligations — meaning that fintech AI providers must be able to demonstrate compliance with BDDK's model governance expectations even though they are not directly subject to BDDK supervision. Practice may vary — verify current BDDK model risk management guidance and the specific model validation requirements applicable to the AI system type before any AI deployment in the Turkish financial services sector.
A Turkish Law Firm advising on TITCK compliance for medical AI must explain that AI systems used in Turkish clinical settings that meet the regulatory definition of medical devices — including AI systems for diagnostic imaging analysis, clinical decision support, drug interaction checking, and patient risk stratification — require conformity assessment and registration with the Turkish Medicines and Medical Devices Agency (TITCK) before they can be legally marketed or used in clinical practice. Turkey's medical device regulation implements the EU Medical Devices Regulation (MDR) standards, meaning that CE-marked medical devices (including AI-based medical devices) generally benefit from a streamlined Turkish registration pathway — but CE marking alone is not sufficient for Turkish market authorization, and the TITCK registration process requires specific Turkish-language documentation and may require clinical evidence generated in Turkish patient populations for higher-risk device classifications. For AI systems that are marketed as "clinical decision support tools" rather than medical devices — in an attempt to avoid the MDR's conformity assessment requirements — TITCK has the authority to reclassify the system as a medical device if its actual function is diagnostic or therapeutic. Practice may vary by authority and year — verify current TITCK medical device classification standards for AI systems and the specific Turkish registration pathway applicable to the AI device's risk classification before any healthcare AI deployment in Turkey.
A lawyer in Turkey advising on BTK compliance for AI in telecommunications and digital platforms must explain that BTK's regulatory framework creates specific compliance obligations for AI systems deployed in telecommunications networks and digital platforms that operate in Turkey. For telecommunications operators, BTK's information security regulation requires that algorithms used for network management, customer service automation, and fraud detection meet information security standards and are subject to BTK's audit rights. For digital platforms subject to Law No. 5651 — which covers social networks, video sharing platforms, and news aggregators above defined Turkish user thresholds — AI-based content recommendation, content moderation, and user profiling systems must comply with the transparency and user rights obligations in Law No. 5651, including: providing users with information about how algorithmic recommendations work; implementing user controls for algorithmic content filtering; and reporting content moderation decision statistics to BTK. Non-compliance with BTK's Law No. 5651 obligations can result in bandwidth throttling — a remedy that makes the platform practically inaccessible in Turkey regardless of its legal status. Practice may vary — verify current BTK and Law No. 5651 AI transparency obligations for digital platforms and the specific content moderation reporting requirements applicable to the platform's user threshold and content type before any AI deployment on a digital platform with Turkish users. The cybersecurity compliance framework relevant to BTK-regulated entities is analyzed in the resource on cybersecurity law in Turkey: compliance obligations for companies.
AI governance frameworks — structure, documentation, and accountability
An Istanbul Law Firm advising on AI governance framework design must explain that an AI governance framework is the organizational and procedural infrastructure that connects the legal compliance obligations — KVKK, sector-specific regulation, consumer protection law — to the operational realities of AI development, deployment, and monitoring within the specific organization. A governance framework without operational integration is a document; an operational AI program without governance documentation is undirected activity. The core structural elements of an effective AI governance framework include: an AI inventory (a comprehensive record of all AI systems in production, their intended use, the data they process, their decision scope, and their current compliance status); an AI risk classification system (applying heightened governance requirements to high-stakes applications in financial services, healthcare, employment, and law enforcement); an AI review and approval process (defining who must approve an AI system before deployment and what documentation they must review); and an AI incident response procedure (distinguishing between AI performance degradation, security incidents, and data protection breaches, and establishing escalation paths for each). Practice may vary — verify current Turkish regulatory documentation expectations for AI governance — specifically KVKK Board, BDDK, and BTK documentation standards — before designing the specific elements of any AI governance framework.
A law firm in Istanbul advising on AI governance roles and responsibilities must explain that effective AI governance requires clearly assigned human accountability for AI system decisions — not in the sense that AI decisions themselves must be made by humans, but in the sense that there must be specific identified individuals within the organization who are accountable for ensuring that the AI system's design, deployment, and monitoring meet the relevant legal and operational standards. The most effective governance structures for AI typically include: a designated AI risk owner (a senior executive accountable for the organization's AI risk posture); a model validation function (technically qualified individuals responsible for reviewing AI systems before deployment against defined standards); a data protection officer (required under KVKK for certain categories of data controllers) who advises on AI data processing implications; and an AI ethics function or committee (reviewing AI applications for bias, fairness, and broader societal impact before deployment). The accountability structure must be documented — in role descriptions, committee charters, and escalation protocols — so that it can be presented to a regulatory authority investigating an AI system failure as evidence that the organization had appropriate human oversight in place. Practice may vary — verify current KVKK Board and sector regulator expectations for human oversight in AI governance before designing any AI governance accountability structure.
An English speaking lawyer in Turkey advising on AI documentation requirements must explain that the documentation burden of AI compliance in Turkey is significant and multi-layered — and the failure to maintain required documentation is itself a compliance violation, independent of whether the underlying AI system operated correctly. The required documentation includes: KVKK processing activity records (mandatory for controllers meeting VERBIS thresholds); privacy impact assessments for high-risk AI processing; data subject transparency information (to be provided at the time of data collection and upon request); data processing agreements with AI vendors; model validation documentation; algorithmic transparency documentation (for regulated sector deployments); and AI incident records (for KVKK breach notification, sector regulator reporting, and potential litigation evidence). We develop AI documentation programs that structure these requirements into a coherent documentation lifecycle — ensuring that each required document is created, maintained, updated at required intervals, and accessible for regulatory review — rather than treating documentation as a post-hoc exercise to be completed when a regulatory inquiry arrives. Practice may vary — check current guidance before acting on any information on this page.
AI contract compliance — vendor management and supply chain obligations
A Turkish Law Firm advising on AI vendor due diligence must explain that a company's AI compliance program extends to its AI supply chain — because a company that deploys an AI system built on a third-party foundation model, trained on data from a third-party data provider, and hosted on a third-party cloud infrastructure is a data controller that is responsible for the KVKK compliance of each of those processing activities, including those conducted by its vendors. AI vendor due diligence should assess: the vendor's own KVKK compliance posture (VERBIS registration, privacy impact assessments, security measures); the contractual basis for any data processing the vendor conducts on the company's behalf (whether a valid KVKK data processing agreement is in place); the vendor's sub-processor chain (whether the vendor uses further sub-processors who are also subject to appropriate contractual safeguards); and the vendor's security incident notification procedures (whether the vendor will notify the company within a timeframe that allows the company to meet its KVKK 72-hour breach notification obligation). We conduct AI vendor due diligence assessments as a standard step in every AI deployment mandate — because the company's KVKK liability does not transfer to the vendor through contract, and a vendor's compliance failure creates direct exposure for the data controller. Practice may vary — verify current KVKK data controller obligations in vendor management contexts and the specific due diligence documentation that the KVKK Board expects before executing any AI vendor contract.
An Istanbul Law Firm advising on AI contract terms for regulatory compliance must explain that the terms of AI deployment contracts must be designed to support regulatory compliance as well as commercial objectives — and the two are frequently in tension. A limitation of liability clause that is commercially standard in international AI contracts may be challenged under TKHK's unfair contractual terms regulation if deployed in a consumer context. A warranty disclaimer that is technically accurate may be inadequate under Turkey's product liability framework if it does not meet the "adequate instruction and warning" standard for a specific AI product category. An arbitration clause designating a foreign forum may be unenforceable against Turkish consumers who have the right to bring claims before Consumer Arbitration Committees and Consumer Courts in Turkey regardless of contract terms. We review AI contracts for both commercial effectiveness and Turkish regulatory compliance simultaneously — because a contract that achieves its commercial objectives while creating regulatory exposure is not a well-drafted contract. Practice may vary — verify current Turkish consumer protection and product liability compliance requirements applicable to AI contracts before finalizing any consumer-facing AI service or product agreement for the Turkish market.
A lawyer in Turkey advising on employment law implications of AI in the workplace must explain that Turkish employers who deploy AI systems in employment contexts — AI hiring tools, performance monitoring systems, AI-based productivity tracking, and algorithmic workforce scheduling — face a specific compliance framework at the intersection of KVKK, the Labor Code (İş Kanunu, Law No. 4857), and the Turkish Constitution's privacy protections. Employee monitoring using AI tools must satisfy KVKK's consent or legitimate interest legal basis requirements, implement data minimization (monitoring only what is necessary for the legitimate purpose), and provide employees with the transparency information required under KVKK Article 10. AI hiring tools that screen applications and make recommendations must be disclosed to applicants as required by KVKK's automated decision-making provisions, and the criteria used by the tool must be capable of demonstration as non-discriminatory under both KVKK and the Labor Code's equal treatment provisions. We design employment AI compliance programs that satisfy both KVKK and Labor Code requirements concurrently — because employment AI is one of the highest-risk AI application categories for simultaneous data protection and discrimination liability. Practice may vary — verify current KVKK and Labor Code requirements applicable to the specific employee AI monitoring or hiring tool before deployment. The employment law framework for foreign employers and HR compliance is analyzed in the resource on foreign worker law in Turkey.
Incident response and regulatory investigation management
An English speaking lawyer in Turkey advising on AI incident response must explain that AI incidents require a specific incident response framework that distinguishes between three categories of incident that have different legal triggers, different notification obligations, and different remediation requirements: (1) AI performance incidents (the AI system produces significantly degraded output quality without a security breach — model drift, adversarial attack, training data staleness); (2) security incidents involving AI (unauthorized access to the AI system's training data, model weights, or inference API — which may constitute a KVKK personal data breach if personal data is compromised); and (3) AI output incidents (the AI system produces a specific incorrect output that causes harm to a specific individual — which may create tort liability, product liability, and consumer complaint obligations simultaneously). Standard IT incident response frameworks typically address only security incidents — they do not address performance incidents or output incidents, which are the most common categories of AI incident in non-adversarial contexts. We develop AI-specific incident response procedures for every AI client that map each incident category to its specific legal trigger, notification obligation, and remediation workflow. Practice may vary — verify current KVKK breach notification requirements, sector regulator incident reporting requirements, and consumer protection complaint response obligations applicable to the specific incident type before designing any AI incident response procedure.
A Turkish Law Firm advising on KVKK Board investigation management must explain that the KVKK Board can initiate investigations of data controllers on its own motion (ex officio) or in response to data subject complaints — and AI-related investigations are an increasing priority for the KVKK Board, which has published decisions specifically addressing automated decision-making, profiling, and cross-border transfer issues in technology contexts. When a KVKK Board investigation is initiated, the data controller is notified and given a defined period to respond with documentation demonstrating compliance. The quality of the response — the completeness of the processing activity records, the clarity of the legal basis documentation, the adequacy of the technical and organizational security measures — determines whether the investigation concludes with a finding of compliance, a warning, or an administrative fine. A data controller that has maintained comprehensive AI compliance documentation throughout its deployment period is significantly better positioned to respond to a KVKK investigation than one that must reconstruct its compliance posture under regulatory time pressure. We manage KVKK Board investigation responses for AI clients — preparing the response documentation, coordinating with technical teams to produce evidence of security measures, and presenting the compliance case to the KVKK Board. Practice may vary — verify current KVKK Board investigation procedure and the specific documentation submission format applicable to AI-related investigations before any investigation response is prepared.
A lawyer in Turkey advising on proactive regulatory engagement for AI must explain that in Turkey's current regulatory environment — where AI-specific regulation is actively developing but not yet comprehensive — proactive engagement with regulators can provide significant compliance advantages over a purely reactive approach. Proactive engagement options include: participating in regulatory consultation processes (the KVKK Board and sector regulators periodically issue draft guidance for public comment, and AI companies that engage substantively in these processes can influence the direction of regulatory requirements and gain early insight into regulatory priorities); applying for regulatory sandbox participation (BTK, BDDK, and TITCK have sandbox programs for innovative technology products that can provide a structured environment for deploying AI systems under regulatory supervision before general market deployment); and initiating voluntary self-assessment programs (proactively assessing the AI system against published regulatory standards and documenting the results can establish a compliance record that favorably positions the company if enforcement action is subsequently initiated by another party). We facilitate proactive regulatory engagement as part of our AI compliance mandate — because early regulatory relationships are a compliance asset that companies without legal representation consistently fail to develop. Practice may vary — check current guidance before acting on any information on this page.
How we work in AI compliance mandates
A best lawyer in Turkey managing an AI compliance mandate begins with a regulatory scope mapping exercise: identifying every regulatory framework that applies to the specific AI system in its specific deployment context. For an AI credit scoring system operated by a Turkish bank: KVKK (personal data processing), BDDK model governance regulation (financial services sector), TKHK (consumer protection for credit applicants), and the Law on Consumer Credit (law-specific obligations for credit decisions). For an AI medical imaging diagnostic system deployed in a Turkish hospital: TITCK medical device regulation (regulatory classification and registration), KVKK (health data processing — a sensitive category), TKHK (patient rights), and the Ministry of Health's health information systems regulation. The scope mapping determines which of the multiple applicable compliance frameworks is the most demanding and which interactions between frameworks create the most significant risks — and this mapping is the foundation for a compliance program that addresses the actual risks rather than the most obvious ones.
ER&GUN&ER advises AI developers, deployers, and operators across the full spectrum of Turkish AI compliance — KVKK processing activity documentation and VERBIS registration, privacy impact assessments for high-risk AI processing, automated decision-making compliance programs, cross-border transfer mechanism design, vendor due diligence and data processing agreement drafting, BDDK model governance compliance, TITCK medical device registration, BTK digital platform obligations, algorithmic transparency documentation, bias audit coordination, AI governance framework design, employment AI compliance, AI contract compliance review, AI incident response procedure development, and KVKK Board investigation management. We work in English throughout all international mandates. For the legal liability framework — covering what happens when AI systems cause harm and how liability is allocated under Turkish law — see the resource on legal liability of AI and automation systems in Turkey. Practice may vary — check current guidance before acting on any information on this page.
Frequently Asked Questions
- Is there a specific AI compliance law in Turkey? No — Turkey does not have a dedicated AI compliance statute. AI compliance obligations are drawn from KVKK data protection law, TKHK consumer protection law, sector-specific regulations from BDDK (banking), TITCK (healthcare), and BTK (telecommunications and digital platforms), and Turkey's National AI Strategy framework. The regulatory landscape is developing — verify current regulatory requirements from each applicable authority before implementing any AI compliance program.
- What are the core KVKK obligations for AI systems processing personal data? Core obligations include: identifying a valid legal basis for each processing activity (KVKK Article 5 or 6 for sensitive data); VERBIS registration for data controllers meeting defined thresholds; providing transparency information to data subjects; implementing appropriate technical and organizational security measures; complying with automated decision-making obligations under KVKK Article 11 (informing individuals, providing human review, explaining decision factors); and notifying the KVKK Board of data breaches within 72 hours. Practice may vary — verify current KVKK Board guidance on AI-specific processing obligations before any deployment.
- What is VERBIS and when must AI processing be registered? VERBIS is the Data Controllers Registry maintained by the KVKK Board. Data controllers that process personal data and meet KVKK Board-defined thresholds (by employee count or annual financial statement size) must register each processing activity, including AI processing activities, with the specific purpose, legal basis, data categories, retention periods, and recipient categories. Generic registration that does not capture AI-specific processing details does not satisfy the obligation. Practice may vary — verify current VERBIS registration thresholds and requirements before filing.
- When is a privacy impact assessment required for AI? While KVKK does not use the term "DPIA" explicitly, KVKK Board guidance indicates that PIAs are required for high-risk processing activities — including AI systems making significant automated decisions, processing sensitive data categories at scale, and involving large-scale profiling. A documented PIA is the most important compliance document for demonstrating good faith in a KVKK investigation. Practice may vary — verify current KVKK Board PIA requirements for the specific processing type before any AI deployment.
- What does KVKK Article 11 require for automated AI decisions? KVKK Article 11 gives data subjects the right to object to decisions made solely by automated processing that produce significant legal or similarly significant consequences. Compliance requires: informing data subjects that automated processing is used; providing the right to request human review; and being able to provide a meaningful (not just technical) explanation of the factors that contributed to the decision. These obligations apply to credit decisions, algorithmic hiring screens, insurance underwriting AI, and medical diagnostic AI recommendations. Practice may vary — verify current KVKK Board automated decision standards applicable to the specific AI system.
- How does BDDK regulate AI in Turkish banking? BDDK requires financial institutions to maintain a model inventory, conduct model validation before deployment, maintain model governance documentation, and implement model risk management for performance degradation. BDDK's outsourcing regulation effectively extends these requirements to AI vendors through the bank's due diligence obligations. Fintech AI providers to Turkish banks must demonstrate compliance with BDDK's model governance expectations even without direct BDDK supervision. Practice may vary — verify current BDDK guidance before any AI deployment in the Turkish financial sector.
- Does TITCK medical device regulation apply to clinical AI? Yes — AI systems for diagnostic imaging analysis, clinical decision support, drug interaction checking, and patient risk stratification that meet the medical device definition require TITCK registration. Turkey implements EU MDR standards, so CE-marked medical AI devices benefit from a streamlined registration pathway — but CE marking alone is not sufficient for Turkish market authorization. AI systems marketed as "clinical decision support tools" to avoid MDR classification may be reclassified as medical devices by TITCK. Practice may vary — verify current TITCK classification standards for the specific AI system before any healthcare AI deployment.
- What are BTK's AI-related obligations for digital platforms? Digital platforms above defined Turkish user thresholds subject to Law No. 5651 must: provide users with information about how AI-based recommendation algorithms work; implement user controls for algorithmic content filtering; and report content moderation decision statistics to BTK. Non-compliance can result in bandwidth throttling. BTK also applies information security requirements to AI systems in telecommunications network management. Practice may vary — verify current BTK and Law No. 5651 AI transparency obligations applicable to the platform's threshold and content type.
- What cross-border data transfer mechanism is valid for AI cloud infrastructure? KVKK Article 9 restricts transfers outside Turkey to countries on the KVKK Board's adequacy list, or to transfers covered by KVKK Board-approved standard contractual clauses (distinct from EU SCCs), or by explicit data subject consent. For AI systems hosted in cloud infrastructure outside Turkey, the transfer mechanism must cover every stage of AI pipeline processing — training, inference, and monitoring — not just the final model output. Practice may vary — verify current KVKK Board adequacy determinations and approved SCC format before any cross-border AI data transfer.
- What does an effective AI bias audit cover? A bias audit systematically tests whether the AI system produces materially different outcomes for different demographic groups that are not justified by the decision's legitimate criteria. It should cover: input data representativeness (whether training data adequately represents the population the system will serve); model performance breakdowns by demographic group; proxy variable analysis (whether model features correlate with protected attributes); and output disparity analysis. Bias audits should be conducted at deployment and at defined intervals during operation. Practice may vary — verify current regulatory bias assessment expectations for the specific AI deployment context.
- What AI governance documents are required? Key documents include: KVKK processing activity records; privacy impact assessments; data subject transparency information; data processing agreements with AI vendors; model validation documentation; algorithmic transparency documentation for regulated sectors; AI incident records; and model governance documentation for BDDK-regulated financial institutions. Each document must be created, maintained, updated at required intervals, and accessible for regulatory review. Practice may vary — verify current documentation requirements for each applicable regulatory framework.
- How should AI employment tools comply with Turkish law? Employment AI (hiring tools, performance monitoring, workforce scheduling) must satisfy KVKK consent or legitimate interest requirements, implement data minimization, provide employee transparency information, comply with KVKK's automated decision-making provisions for hiring recommendations, and demonstrate non-discrimination compliance under the Labor Code. AI hiring tools must disclose their use to applicants and be capable of demonstrating non-discriminatory criteria. Practice may vary — verify current KVKK and Labor Code requirements for the specific employee AI tool before deployment.
- What three categories of AI incident require different response approaches? (1) AI performance incidents — model drift, adversarial degradation, training data staleness — require performance remediation but may not trigger regulatory notification unless personal data is affected; (2) security incidents involving AI — unauthorized access to training data, model weights, or inference API — may constitute KVKK personal data breaches requiring 72-hour Board notification; (3) AI output incidents — specific incorrect outputs causing individual harm — may create simultaneous tort, product liability, and consumer complaint obligations. Standard IT incident response frameworks address only security incidents. AI-specific procedures must address all three categories.
- Can Turkish companies participate in AI regulatory sandboxes? Yes — BTK, BDDK, and TITCK have sandbox programs that allow structured deployment of innovative technology products under regulatory supervision before general market deployment. Sandbox participation provides early regulatory insight, a structured testing environment, and a compliance track record that favorably positions the company if enforcement action arises later. We facilitate sandbox applications as part of proactive regulatory engagement programs for AI clients. Practice may vary — verify current sandbox program conditions and application requirements for the relevant sector regulator.
- What is the difference between AI compliance and AI liability management? AI compliance is the proactive program — building the governance framework, documentation systems, data protection measures, and regulatory relationships that prevent violations from occurring. AI liability management is what applies when violations have occurred or when harm has resulted — determining who bears legal responsibility, challenging enforcement actions, defending litigation, and pursuing contractual remedies in the supply chain. Effective compliance significantly reduces liability exposure, but cannot eliminate it entirely. The liability framework is analyzed in the companion resource on legal liability of AI and automation systems in Turkey.
Author: Mirkan Topcu is an attorney registered with the Istanbul Bar Association (Istanbul 1st Bar), Bar Registration No: 67874. His practice focuses on cross-border and high-stakes matters where evidence discipline, procedural accuracy, and risk control are decisive.
He advises AI developers, operators, and regulated entities across KVKK AI Data Processing Compliance, VERBIS Registration, Privacy Impact Assessments, Automated Decision-Making Compliance Programs, Cross-Border Transfer Mechanisms, BDDK Model Governance, TITCK Medical AI Registration, BTK Digital Platform Obligations, Algorithmic Transparency Documentation, Bias Audit Programs, AI Governance Framework Design, Employment AI Compliance, AI Vendor Management, AI Incident Response Procedures, and KVKK Board Investigation Management matters where proactive compliance architecture and regulatory documentation are decisive.
Education: Istanbul University Faculty of Law (2018); Galatasaray University, LL.M. (2022). LinkedIn: Profile. Istanbul Bar Association: Official website.