The Complete Guide to Using AI as a Legal Professional in Turkey in 2025

AI is no longer a theoretical debate for Turkish lawyers - it's reshaping how cases are researched, contracts are drafted and financial institutions prevent fraud, with one bank reporting a 98.7% reduction in fraud-related losses and systems analysing roughly 40 million transactions a day to flag about 500 potential cases, underscoring the scale of change in Türkiye's finance sector and the need for compliance-savvy counsel (see Türkiye's National AI Strategy and regulatory updates).

Regulators and bodies are actively updating guidance on data localisation, chatbots and automated decision‑making, so legal teams must pair technical literacy with risk controls to advise on data protection and liability gaps highlighted in recent legal trend reports for 2025.

Practical, job-focused training - like the AI Essentials for Work bootcamp - can help lawyers learn promptcraft, tool workflows and governance basics quickly, turning AI from a compliance headache into a productivity advantage for firms and in‑house teams alike.

Program	Length	Early bird Cost	Syllabus
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work bootcamp syllabus - Nucamp

Türkiye's AI policy is anchored in the National Artificial Intelligence Strategy (NAIS 2021–2025), a government roadmap prepared by the Digital Transformation Office and the Ministry of Industry and Technology that bundles six strategic priorities - skills, R&D and innovation, data and infrastructure, legal and administrative adaptation, international cooperation, and workforce transformation - into 24 objectives and 119 concrete measures to build an “agile and sustainable AI ecosystem” (see the full strategy for background and governance details).

The NAIS stresses secure data sharing through a Public Data Space, public AI platforms and regulatory sandboxes to accelerate testing and commercialisation, and it explicitly targets outcomes such as raising AI's contribution to GDP to 5% and growing AI employment to 50,000; recent updates refined the program with a focused 2024–2025 action plan prioritising generative AI, Turkish large language models and high‑performance computing capacity.

For legal teams, two policy takeaways matter: the state is actively shaping data governance and public procurement to favour domestic AI solutions, and parallel work on algorithmic accountability, transparency standards and a “trustworthy AI” seal signal rising expectations for explainability and institutional controls across public-sector deployments - monitor the DTO's circulars and the action‑plan updates to spot immediate compliance triggers and sandbox opportunities.

NAIS 2025 Goal	Target
Contribution of AI to GDP	5%
Employment in AI	50,000 people
AI employment in public institutions	1,000 people
Graduate-level AI diploma holders	10,000
Priority in public procurement	Local AI applications prioritised
International ranking	Top 20 in AI indices

“This should not be perceived as a new strategy, but rather as a refinement of the previous year's planning,”

Türkiye's AI program is increasingly a patchwork of state-sponsored R&D threads, academic pipelines and hands‑on upskilling that legal teams should watch closely: conversations about a

TÜBİTAK Bilgem Turkish LLM

- framed by commentators as weighing

the good, the bad, and the ugly

of large language models - signal government and research interest in domestically‑relevant models and policy debate (SETAV analysis of the TÜBİTAK Bilgem Turkish LLM); at the same time, Turkey's law schools are expanding tech and information‑law curricula (Istanbul Bilgi, Koç, Bilkent and others appear in 2025 program listings), creating a steady supply of lawyers trained to bridge law and AI (Top LL.M. programs in Turkey (2025 listings)).

Complementing research and education, national policy frameworks push knowledge exchange and commercialisation of research infrastructure - efforts captured in Türkiye's science, technology and innovation dashboards that prioritise co‑creation between universities, industry and government.

For practising lawyers that means practical projects, pilot procurements and tool selection will dominate the near term; pairing technical pilots (for example, explainable assistants such as Claude) with clear governance beats off compliance risk and turns pilot results into usable advice for clients (Top 10 AI tools for Turkish legal practice (2025)).

Picture a classroom, a ministerial lab and a boutique firm all testing the same Turkish‑language prompt - and the gaps between them are where lawyers add value.

Türkiye's formal steps toward an AI-specific statute remain at an early stage: a Draft Law on Artificial Intelligence was prepared by a parliament member and submitted to the Grand National Assembly, signalling that lawmakers are moving from strategy to statute (see the legislative update from GÜN AV).

Because the public record on the draft's text and timetable is thin, Turkish legal teams should track committee publications and DTO circulars closely and be ready to map any new obligations onto existing frameworks like KVKK and the National AI Strategy; watching international comparators helps, since jurisdictions nearby are already setting firm timelines and enforcement mechanisms - for example, Texas enacted the Responsible Artificial Intelligence Governance Act on June 22, 2025 (effective January 1, 2026), creating prohibitions, a regulatory sandbox and an AI council that illustrate the kinds of clauses Turkish drafters may consider or reject.

The practical takeaway for counsel: prioritise horizon‑scanning and impact assessments now - a single definition or prohibition (for instance on social scoring or biometric identification) can reshape public procurement and malpractice risk overnight, so treat the draft as a compliance trigger rather than a distant policy paper.

"any machine-based system that, for any explicit or implicit objective, infers from the inputs the system receives how to generate outputs, including content, decisions, predictions, or recommendations, that can influence physical or virtual environments."

For Turkish lawyers advising on AI projects, data protection is the operational drill: map whether an AI workflow handles personal or sensitive data under Law No.

6698, register controllers in VERBIS where required, and build DPIAs into every pilot because the KVKK has specific guidance on biometric processing and the “right to be forgotten” that changes how models can ingest identity signals - see the KVKK guidelines for practical checkpoints (KVKK biometric processing and right to be forgotten guidelines (Turkish DPA)).

The LPPD's core rules - lawful basis, purpose limitation, data minimisation and strong security measures - are summarised in practitioner guidance and flag hard limits on cross‑border transfers unless adequacy, SCCs or explicit consent are in place, so counsel should treat data flows as contract and compliance risks, not just technical choices (Overview of Turkey LPPD, VERBIS registration and cross-border transfer rules).

Where automated decision‑making is involved, the DPA's 2021 Recommendations encourage human oversight, alternatives to fully automated outcomes and project‑specific privacy programs - practical steps are simple but non‑negotiable: anonymize where possible, document role (controller vs processor), prepare breach playbooks (72‑hour notification) and remember enforcement can include fines in the multi‑million TRY range and even criminal penalties, so frame AI pilots as regulated products from day one (2021 Turkish DPA recommendations on AI, automated decision‑making and oversight).

“Any information relating to an identified or identifiable natural person.”

Using AI in Turkish legal practice reshapes long‑standing duties: lawyers remain the ultimate gatekeepers for validity, client consent and confidentiality, so a draft produced by a model without a clear human review trail can trigger malpractice, unauthorized‑practice claims under Article 35 of the Attorneys Act, and evidentiary challenges if authorship or intent are disputed - issues explored in Istanbul Law Firm's practical guidance on AI contract drafting in Turkey (Istanbul Law Firm practical guidance on AI contract drafting in Turkey).

Turkish law also treats AI as non‑person - liability attaches to operators, developers or deploying firms - so firms must define roles, indemnities and incident processes in supplier and engagement contracts, adopt human‑in‑the‑loop checkpoints, keep detailed creation and approval logs, and incorporate KVKK privacy safeguards and DPIAs to avoid data‑training and cross‑border transfer exposure; these themes echo the national landscape described in the Turkey AI practice guide (Chambers 2025 Turkey artificial intelligence practice guide).

Practical defenses include clear client disclosure clauses, robust oversight policies, insurance and contractual risk allocation, plus court‑ready authentication procedures - because in practice, a single unchecked prompt or missing approval stamp can turn a speedy AI draft into a costly professional‑responsibility problem.

Put simply: AI already does the heavy lifting in everyday Turkish legal workflows - drafting first‑pass contracts, extracting clauses for diligence, triaging NDAs and surfacing non‑standard terms - but the value for Turkish practitioners comes from pairing those tools with clear safeguards.

Use contract‑review agents that embed firm playbooks and risk scores (see Juro's 2025 guide to AI contract review) to speed redlines and approvals, deploy explainable assistants such as Claude for Turkish‑language regulatory and privacy checks, and always bake in DPIAs, anonymisation, VERBIS registration where required, and human‑in‑the‑loop checkpoints so a lawyer signs off before any document is final.

Operationally that means logging metadata, version history and approval stamps so an AI‑drafted agreement can be proven in court rather than challenged for

“authorship uncertainty”

- a courtroom‑ready chain‑of‑custody approach described in Istanbul Law Firm's practical guidance - and carving liability, indemnities and service levels into vendor contracts while coordinating insurance and incident playbooks.

The memorable test: if a judge asks

“who approved this clause?”

the answer must be a named attorney and a timestamped audit trail, not

“the model said so”

build workflows to make that answer routine, not exceptional.

Procurement and vendor management are now front‑row compliance issues for Turkish legal teams: public tenders and procurement policies increasingly favour certified, local or compliance‑ready AI suppliers, so contract clauses that once seemed boilerplate - data‑training rights, subprocessor chains, audit access and indemnities - must be rewritten as active risk controls rather than afterthoughts (see Nemko guide to AI regulation in Turkey for procurement incentives and certification routes).

Practical steps are familiar but non‑negotiable: require KVKK‑aligned data processing schedules, VERBIS registration where controllers are involved, detailed cross‑border transfer mechanisms (adequacy findings, standard contractual clauses or explicit consent) and robust logging and audit rights to prove human oversight.

Vet cloud and model vendors for bias‑testing, explainability guarantees and incident response SLAs; negotiate liability caps and turnover‑based fines off the table - Turkey's draft enforcement regime contemplates heavy penalties for prohibited or non‑compliant AI use.

For international stacks, a single permissive transfer clause can turn a pilot into a multi‑million‑TL enforcement headache, so work closely with English‑and‑Turkish counsel to align jurisdictional law, data localisation expectations and contractual dispute mechanisms (see Istanbul Law Firm vendor-contract checklist and TermsFeed KVKK and GDPR transfer overview).

Treat procurement as a governance exercise: a signed contract plus a timestamped DPIA and a named point‑of‑contact are the best defence when regulators or clients demand proof of control.

“computer-based systems that are able to carry out human-like skills such as learning, rationalization, problem solving, perception, semantic comprehension and cognitive functions.”

Sectors in Türkiye are not on the same AI timetable: finance leads the pack with banks and fintechs already running large‑scale detection systems - one bank reports a 98.7% reduction in fraud losses after deploying AI that sifts roughly 40 million transactions a day to flag around 500 potential cases - so counsel advising lenders must stitch together BRSA‑grade IT outsourcing rules, the IS Regulation expectations and strict local‑storage clauses into vendor contracts (see BRSA compliance guidance and cloud provider mappings).

Health and public‑sector uses raise different pressure points: chatbots and automated triage tools trigger the Turkish DPA's disclosure and child‑protection notes, meaning age verification, retention limits and clear controller IDs are non‑negotiable; meanwhile the state's NAIS and procurement bias toward domestic solutions push explainability and a “trustworthy AI” posture for public deployments, making procurement teams and legal counsels co‑owners of compliance.

Defence and sensitive‑infrastructure projects heighten both national‑security procurement controls and liability debates - since AI lacks legal personality, responsibility will remain with developers, operators or contracting agencies, amplifying the need for DPIAs, strict audit rights and insurance.

For sectoral risk management in 2025, practical controls - localisation clauses, human‑in‑the‑loop gates and documented sign‑off trails - are the single best hedge against regulatory and reputational shocks (see recent legal trend analysis in Türkiye for granular updates).

Metric / Requirement	Value / Note
Reported fraud reduction (leading bank)	98.7%
Transactions analysed (approx.)	40,000,000 per day
Potential fraud cases flagged (approx.)	500 per day
Banking data rule	Customer and chatbot data must be stored in Türkiye (localisation & contractual clauses)

As this guide closes, the practical bottom line for Turkish legal teams is simple: treat AI projects as regulated products from day one and convert policy risk into repeatable controls - monitor the AI bill and DTO circulars, run KVKK‑aligned DPIAs and VERBIS checks for any personal or biometric data, lock human‑in‑the‑loop sign‑off into workflows, and bake vendor clauses for data‑training, audit access and cross‑border transfers into every contract; if a judge asks “who approved this clause?” the answer must be a named attorney and a timestamped trail, not “the model said so.” Prioritise bias testing, explainability documentation and incident playbooks, consider sandbox entry for high‑risk pilots and keep governance at board level with an AI steering committee and periodic audits.

For practical templates and sectoral nuance, start with Turkish practice guides such as Istanbul Law Firm's AI compliance overview and the KVKK guidance on biometric processing and data subject rights, and close skills gaps fast with targeted courses like Nucamp AI Essentials for Work bootcamp to train lawyers on promptcraft, DPIAs and tool workflows so compliance becomes operational, not aspirational.

Checklist Item	Practical Action
DPIA & VERBIS	Assess data flows, register controllers where required
Human review & audit logs	Timestamped approvals, version history, court‑ready chain of custody
Vendor & procurement clauses	Data‑training rights, SCCs/adequacy, audit access, indemnities
Bias & explainability	Pre‑deployment tests, model summaries and decision logs
Governance & training	AI committee, incident playbook, staff upskilling

computer-based systems that are able to carry out human-like skills such as learning, rationalization, problem solving, perception, semantic comprehension and cognitive functions.