Generative AI in Turkey: Adoption Rates, Market Landscape and Regulation

Where does generative AI in Turkey stand today?

Generative AI in Turkey refers to the fast growing use of models that create text, images, audio and code by individuals, companies and public bodies, all within a legal framework that still has no dedicated AI law. Personal use is spreading quickly, while business adoption remains limited.

I have worked in digital marketing since 2012, based in Istanbul. I watched search engines, social media and mobile reshape the industry. Generative AI, however, has spread faster than any of those waves. In this article I want to give you a clear picture of the Turkish market: who uses these tools, how the market looks and where regulation is heading.

I rely only on figures that official institutions publish. Where no reliable number exists, I do not guess. Instead, I label my field observations clearly as observations. That way you can always tell measured data apart from interpretation, which matters a lot when you plan a market entry or a compliance project.

What exactly does generative AI cover?

Generative AI is the umbrella term for systems that learn patterns from training data and produce new content. Chat assistants, image generators, voice tools and coding assistants all fall under it. If you want the technical background, my article on large language models (LLMs) explains the architecture in detail.

In the Turkish context, one point stands out: most users rely on global tools rather than local ones. ChatGPT, Gemini, Claude, Microsoft Copilot and Perplexity have become almost synonymous with "AI" in everyday Turkish. As a result, the local debate often centres on Turkish users sending data to systems that companies operate abroad.

• Text: email drafts, report summaries, product descriptions, translation.
• Images and video: campaign drafts, product photo variations, short clips.
• Audio: voiceovers, transcription, call centre automation.
• Code: completion, test writing and debugging inside software teams.

How many people use generative AI in Turkey?

The most reliable source is TÜİK, the Turkish Statistical Institute. In its 2025 household ICT usage survey, TÜİK measured generative AI use as a separate question for the first time. According to that survey, 19.2 percent of individuals aged 16 to 74 said they had used generative AI in the previous three months. In other words, roughly one in five people has tried these tools.

The age breakdown, however, tells a sharper story. Among 16 to 24 year olds the share rises to 39.4 percent. Next, it stands at 30 percent for ages 25 to 34 and at 15.5 percent for ages 35 to 44. Private and personal purposes lead with 79.7 percent of users. Professional use reaches 33.8 percent, and formal education 31.4 percent.

So my reading is simple: AI first spread through personal phones and private life in Turkey, while the move into the workplace runs slower. You can find the latest releases in the TÜİK science, technology and information society category. Because the figures change every year, check the newest bulletin before you make decisions.

How far have Turkish companies adopted AI?

The corporate picture looks more cautious. According to the TÜİK survey on ICT usage in enterprises, the share of enterprises that use at least one AI technology rose from 2.7 percent in 2021 to 7.5 percent in 2025. That is real growth; however, the share remains low.

Company size also makes a big difference. The rate stands at 6.6 percent for enterprises with 10 to 49 employees and 9.6 percent for those with 50 to 249. For large enterprises with 250 or more employees, it climbs to 24.1 percent. In short, large firms experiment quickly while small and mid sized businesses lag behind.

• Marketing and sales lead among enterprises that use AI, at 46.5 percent.
• Production processes follow at 41.1 percent, and R&D at 41.0 percent.
• Business administration processes rank fourth at 40.0 percent.
• Among enterprises with no plans to use AI, 74.2 percent name lack of expertise as the main barrier.

That last point matters most to me. The obstacle is neither money nor technology; it is knowledge and process design.

Why is the gap between personal and business use so large?

Personal experiments cost little, while corporate experiments cost a lot. A student can open the free version of ChatGPT in the evening and close it again. A company that uses the same tool, on the other hand, faces questions about data security, contracts, staff training and liability. Therefore companies move slower.

I also often see "shadow AI" in the field. The company sets no official policy, yet employees paste client emails, proposals and even spreadsheets into these tools through personal accounts. As a result, actual usage may run higher than the official numbers suggest. I share this as an observation, not as measured data.

That said, the gap also opens an opportunity. Because most competitors still do not use AI in a structured way, a small business that organises its processes early can gain a real time advantage. The condition, however, is to move from random trials to a written usage policy.

What does the market for generative AI in Turkey look like?

You can view the market in three layers. The first layer holds the global model providers; most users access their apps directly. The second layer includes Turkish software companies, banks, telecom operators and e-commerce platforms that embed these models into their own products. Finally, the third layer covers consulting, integration and training services, which keep growing.

Many market size figures circulate online; however, they come from private research firms that use very different methods. Because these estimates diverge sharply, I do not put a single number in this article. In practice, looking at concrete use cases in your own sector helps you far more than a general market forecast.

For marketing, the most visible impact shows up in search. Turkish users now ask part of their questions to ChatGPT or Gemini instead of Google. I covered the effect on brands in my article on how your brand shows up in ChatGPT and Gemini.

Why do Turkish language models and local startups matter?

Global models understand Turkish better every year, for example in everyday chat. Still, agglutinative grammar, local idioms and legal terminology can challenge them. For this reason, models that developers train or fine tune on Turkish data carry strategic weight, especially in the public sector, law and finance.

In addition, the state targets this area openly. The National Artificial Intelligence Strategy from the Presidency's Digital Transformation Office, together with its updated 2024 to 2025 action plan, lists the development of generative AI technologies, Turkish language models and value added products built on large language models among its priorities. Beyond that, the plan aims to widen access to high performance computing and data.

For a business, the practical question is simple: a local model or a global one? The answer depends on how sensitive your data is, your budget and the quality you need. For organisations that process sensitive customer data, where the data travels matters as much as model quality.

Does Turkey have a law that regulates generative AI?

The short answer is no, not yet. Turkey has no AI specific law in force. Instead, existing legislation applies. Law No. 6698 on the Protection of Personal Data (KVKK) covers personal data. The Law on Intellectual and Artistic Works covers copyright, while e-commerce and consumer rules cover commercial communication and customer rights.

Members of parliament have submitted several AI related bills to the Grand National Assembly (TBMM) over different periods. These bills address labelling of deepfake content, provider liability and administrative sanctions. However, a bill has no binding force until it becomes law. For that reason, treat any article that presents bill texts as current rules with caution.

In addition, parliament ran a research commission on artificial intelligence. Its recommendations may signal the direction of a future law. Even so, a company's compliance work today should rest on the laws in force and on the guidance that the Turkish data protection authority publishes.

What does the KVKK guide on generative AI tell companies?

On 24 November 2025, the Turkish Personal Data Protection Authority published a guide titled Generative AI and the Protection of Personal Data (in 15 Questions). The guide explains how these systems produce content, their life cycle, use cases and risks. It then assesses personal data processing through these systems under Law No. 6698.

For companies, the key message reads like this: whoever acts as data controller for personal data processed during the development or use of generative AI carries the legal obligations. So saying "a foreign company runs the tool" does not remove your responsibility.

Moreover, the guide also gives advice to individuals and to parents. A separate section covers steps parents can take to protect children's personal data when they use these tools. I find it useful to add that section to staff training as well, since employees are often parents too.

Which compliance steps should companies take under KVKK?

When you read the guide together with the law, a practical checklist emerges. The steps below do not replace legal advice; however, they give you a solid framework to start the internal discussion.

1. Build an inventory: which team uses which tool with which data?
2. Classify data: identity data and special categories such as health data should never enter free tools.
3. Review cross border transfers: document where the tool processes data and how you meet KVKK transfer rules.
4. Update privacy notices: state clearly if AI processes personal data.
5. Use business accounts: prefer plans that let you opt out of model training.
6. Train staff: explain with concrete examples what they must never paste.

If your team also handles email with clients, make sure it runs on a proper company domain. I explained why in my guide to business email on a custom domain.

How does the EU AI Act affect companies in Turkey?

The EU AI Act does not apply directly in Turkey. Its scope, however, reaches beyond EU borders. Providers that place AI systems on the EU market, or whose system output people use in the EU, can fall within scope regardless of where they sit. Therefore Turkish software and service exporters to Europe need to follow the Act closely.

As the European Commission's regulatory framework page on AI explains, the Act takes a risk based approach. It bans practices with unacceptable risk, places strict duties on high risk systems and sets transparency rules for certain others. For example, users should know when they talk to an AI, and providers should mark AI generated content.

The obligations phase in over several years, and EU institutions have discussed postponing some dates. So instead of memorising a timeline, check the Commission's official page regularly before you plan a product launch in Europe.

How do the Turkish and EU approaches compare side by side?

Comparing both approaches clarifies in which order you should build your compliance plan. The table below gives a general framework; it does not replace legal advice.

In practice, I recommend this order: first build solid KVKK compliance, because it applies in every case. Then, if you sell into the EU, review the scope of the AI Act separately. That way you prepare for both frameworks without doing the work twice.

What should you watch regarding copyright, deepfakes and ownership?

First, copyright remains one of the most debated topics. Turkish law builds authorship on human creativity. Consequently, the question of who owns output that an AI produces on its own still has no clear answer in Turkey. This uncertainty creates risk, especially for agencies and content creators.

For deepfakes, however, existing law already applies. Using someone's voice or image without consent can raise issues under personality rights, data protection and, depending on the case, criminal law. The bills in parliament also highlight the idea of labelling such content.

• Get written consent before you generate a real person's voice or face for an ad.
• Read the commercial use terms of every image tool you use.
• State AI use in your client contracts where relevant.
• Keep core brand assets, such as logos and key visuals, under human designer control.

Where do Turkish companies use generative AI most?

TÜİK data puts marketing and sales first, and my field experience matches that. In projects my team and I run, these are the most common use cases:

• Content drafts: blog posts, product descriptions, social media copy.
• Customer communication: answer drafts for frequent questions, call summaries.
• Ad variations: alternative headlines and descriptions.
• Reporting: interpreting data tables and preparing summaries for managers.
• Software: code completion and test writing.

I covered how to position AI on your own website in how to use AI on your website, and the design side in AI in web design and automation. I will not repeat those points here.

How is generative AI in Turkey changing search and SEO?

Meanwhile, search behaviour keeps shifting. Google AI Overviews, ChatGPT Search and Perplexity give users direct summary answers, and Turkish queries feel this too. Especially for informational searches, I see part of the clicks fading on many sites.

However, this does not mean SEO is over. On the contrary, clear, accurate and structured content that AI tools can cite gains value. I explain the approach in my article on generative engine optimization (GEO). For the technical side, the llms.txt generator and the robots.txt generator help you prepare settings for AI crawlers quickly.

In short, the question for Turkish brands is not "Google or AI?". The right question is this: does my content appear as a trusted source in both channels?

How does generative AI use differ by sector in Turkey?

In practice, the pace differs clearly between sectors. The examples below do not form an official ranking; I compiled them from public announcements and my own field observations.

• Banking and finance: banks develop virtual assistants, request classification and internal document search. Because regulation is strict, they usually work in closed environments.
• E-commerce: product descriptions, category copy and review summaries lead.
• Telecom: call centre automation and support reply drafts stand out.
• Education: students use the tools heavily, while institutions work on ethical use rules.
• Public sector: the national strategy expects public institutions to lead AI projects in citizen services.

If your sector does not appear here, do not worry. The core question stays the same everywhere: which repetitive task saves the most time with the least risk? Once you answer that honestly, your first project becomes obvious.

Where should small businesses start with AI?

Since lack of expertise forms the biggest barrier, the starting point should be training plus a small pilot. Rather than launching a major transformation, pick one measurable process.

1. Identify the repetitive writing task that takes the most time each week.
2. Choose one tool for it with a business account.
3. Test it for two weeks with examples that contain no personal data.
4. Measure time spent before and after.
5. Make human review of every output a fixed rule.
6. If results look good, move to a second process with a written policy.

This approach keeps both cost and risk low. Moreover, it reduces anxiety within the team, because employees experience the tool as a helper that lightens their workload rather than as a threat.

How can you manage accuracy and bias risks?

First, generative models produce text based on probability. As a result, they can state wrong facts with full confidence. The risk grows for Turkey specific topics, because Turkish sources make up a smaller share of training data than English ones. For instance, if you ask about a current regulation or a tax rate, you may get an outdated or invented answer.

Bias, on the other hand, forms a separate issue. The KVKK guide draws attention to processing risks that can lead to discriminatory outcomes. Especially in hiring, credit scoring and pricing, I advise you never to let AI act as the sole decision maker.

1. Verify every output that contains regulations, prices or statistics against a primary source.
2. Leave the final word to a person in any process that decides about people.
3. Log wrong outputs and share them with the team regularly.
4. Ask the same question in different tools to check consistency.

These steps may seem slow. Yet the damage that a single wrong fact can do to your brand costs far more than a few extra minutes.

What should a corporate AI usage policy include?

A written policy remains the most effective way to reduce shadow AI. You do not need a long legal text; a clear two page document with examples suffices for most small businesses. Still, I strongly recommend that a lawyer reviews it.

• Approved tools: the list of tools and account types the company allows.
• Prohibited data: a clear list of identity, health, financial and trade secret data.
• Approval flow: who performs the final check on external content.
• Labelling: how you mark AI generated images and audio.
• Training: a short onboarding session for new staff.
• Review: a commitment to revisit the policy at least once a year.

Above all, keep the language plain. A policy that nobody reads protects nobody, so short sentences and real examples from your own workflow matter more than legal completeness.

How can you build AI literacy in your team?

In the TÜİK data, lack of expertise stood out as the main barrier. Therefore the real investment should go to people, not tools. AI literacy means knowing what a tool can do, where it fails and which data it must never see.

In practice, I suggest this method. First, pick one volunteer from each team and give them time to explore. Next, let that person run a short workshop with real examples from the team's own work. Working on the team's own emails, reports and client questions delivers far more lasting results than generic training videos.

• Share the "most useful prompt" within the team every month.
• Share failed attempts too; mistakes teach best.
• Managers should use the tools as well, otherwise the policy stays on paper.
• Test new features with a small group first.

Also, this approach changes how employees see AI. They start to view the tool not as a rival but as a helper that takes over the dull parts of their job.

What could change for generative AI in Turkey next?

Rather than making firm predictions, I prefer to share the signals worth tracking. First, watch how the AI bills and the research commission's recommendations turn out. A dedicated AI authority or law would directly change the compliance load for companies.

Second, watch how fast KVKK updates its guidance and applies it through concrete decisions. Third, follow the resources that the next phase of the national strategy allocates to Turkish language models and computing infrastructure. In addition, a clearer AI Act timeline in the EU will matter a lot for Turkish exporters.

On the usage side, TÜİK's annual data will offer the best indicator. High usage among young people suggests that business adoption will speed up as this generation enters the workforce. That is not a forecast; it is the natural reading of current data.

How should you shape your digital marketing strategy in this shift?

Generative AI changes both the production and the distribution side of marketing. So I recommend thinking in two axes. On the internal axis, you produce faster and more consistently with AI. On the external axis, you make sure AI answers and classic search both represent your brand correctly.

In our SEO consulting work, my team and I handle both axes together. On the advertising side, during Google Ads management, we run AI generated variations through human review before we test them. If you want a quick look at your current site, try the SEO checker.

Also, protect your brand voice. Tools write fast, but the tone, examples and point of view that set you apart still come from your team.

My final word: the race for generative AI in Turkey is still at an early stage. Most companies have not even started. Therefore a business that builds a structured, measurable and KVKK compliant process today will hold a clear advantage in the years ahead.