A One-Week Arabic and Turkish AI Quality Check

Most AI tools work in English before they work well in Arabic or Turkish. A response can be grammatically correct and still sound unnatural, use the wrong level of formality, misunderstand a local phrase or give an answer your team would never approve.

You do not need a large AI project to reduce these problems. This week, you can build a small language-quality test using real customer questions, approved answers and clear escalation rules.

Start with one customer journey

Do not test every possible use case at once. Choose one journey where language quality affects revenue or customer trust.

Good starting points include:

• Product questions before purchase
• Delivery and return questions
• Appointment requests
• Hotel, clinic or restaurant enquiries
• Support questions received through WhatsApp, Instagram or your website

Pick one market and one language first. For example, a Türkiye-based store might begin with Turkish product and delivery questions. A Gulf business might start with Arabic customer support for one product category.

The goal is not to prove that AI can speak Arabic or Turkish. The goal is to decide whether it can handle a defined set of customer conversations without creating unnecessary work for your team.

Build a small, realistic test set

Collect 30 to 50 real questions from your support inbox, social media messages, sales team or website chat. Remove names, phone numbers, order numbers and other personal details before putting the content into an AI tool.

If you do not have enough historical questions, write realistic examples based on your most common enquiries. Label these as test examples so nobody later mistakes them for customer data.

Include different levels of difficulty:

• Short questions such as “Kargo ne zaman?” or “هل يوجد توصيل؟”
• Misspellings and missing punctuation
• Regional vocabulary and informal phrasing
• Questions mixing Arabic or Turkish with English product terms
• Requests that require information from your catalogue or policies
• Questions the AI should not answer without a human

For Arabic, decide which variety you are testing. Modern Standard Arabic may be suitable for formal information, while customers may write in Gulf, Egyptian, Levantine or another dialect. You do not need to support every dialect immediately, but you should identify the market you actually serve.

For Turkish, test everyday customer language rather than only polished textbook sentences. Customers may use abbreviations, local spelling habits or short phrases that rely heavily on context.

Score meaning, tone and action separately

A single “good or bad” score hides useful problems. Review every answer using four simple criteria.

1. Meaning

Did the AI understand the question? Check product names, quantities, dates, prices, delivery areas and return conditions carefully.

A fluent answer with the wrong delivery period is not a language success. It is a business risk.

2. Local naturalness

Would a local customer describe the answer as normal and respectful? Look for direct translations, strange sentence order, excessive formality and words your customers do not use.

Ask a native-speaking employee or trusted reviewer to mark responses as natural, understandable but awkward or unclear. If you do not have that capability internally, arrange a short review with a qualified native speaker who understands your industry.

3. Brand tone

Decide how your business should sound. A medical clinic, luxury retailer and delivery company should not use the same tone.

Write three to five rules, such as:

• Use polite Turkish without sounding bureaucratic
• Use clear Arabic and avoid unexplained technical terms
• Keep answers warm but do not use exaggerated promises
• Use the customer’s preferred language when they switch languages
• Ask one clarifying question instead of guessing

4. Next action

Every useful answer should move the customer forward. That might mean showing a product link, requesting an order number, offering appointment times or transferring the conversation to a person.

Mark any response that gives information but leaves the customer unsure what to do next.

Add safety and regulation checks

Language quality is only one part of a customer-facing AI review. Before connecting the assistant to live channels, check how it handles personal information and sensitive requests.

For Türkiye, review your workflow against the requirements of the Personal Data Protection Law, commonly known as KVKK, with appropriate legal advice. In MENA, requirements differ between countries and may involve consent, privacy notices, data storage, cross-border transfers, retention and sector-specific restrictions.

You do not need to solve every legal question in a language test. You do need to document the basics:

• What customer data does the system receive?
• Why is each piece of data needed?
• Where is it processed or stored?
• How long is it retained?
• Can a human review or correct the result?
• Which questions must always go to a trained employee?

Do not let the assistant diagnose medical conditions, make credit decisions, promise legal outcomes or invent policy exceptions. Create an approved response for each sensitive category and define the handoff process.

This is operational guidance, not legal advice. If the system will process sensitive data or operate across borders, ask local counsel to review the design before launch.

Run a five-day language QA sprint

A small team can complete the first review in one working week.

Day 1: Choose the scope

Select one customer journey, one market and one channel. Gather your 30 to 50 test questions and remove personal information.

Day 2: Write the reference answers

For each question, write the answer your team would want customers to receive. Include the source of important facts, such as a delivery policy or product specification.

Day 3: Test the AI

Run the questions in Arabic, Turkish and, where relevant, mixed-language versions. Save the exact prompts and responses. Do not rely on memory or screenshots scattered across different tools.

Day 4: Review and classify failures

Group problems into categories: translation, missing context, incorrect business fact, tone, privacy or escalation. Fix the highest-risk categories first.

Day 5: Update and retest

Improve the instructions, knowledge base or escalation rules. Run the same test set again and record what changed. Keep failed examples as regression tests for future updates.

A practical review checklist

Before allowing the AI to answer real customers, confirm that:

• Business facts are current, especially prices, stock, delivery and returns
• Arabic and Turkish responses sound natural to a qualified native reviewer
• The assistant does not guess when information is missing
• Sensitive requests are escalated to a human
• Personal data is minimised and handled according to your approved process
• The customer gets a clear next step in every normal conversation
• Failed examples are saved for future testing

For example, if a store handles 300 customer questions each week, it could begin by reviewing the 40 questions that appear most often or create the most manual work. That is enough to find recurring language and workflow problems without trying to audit the whole business at once.

How ADMOV can help

ADMOV can help you design and connect an Arabic or Turkish AI workflow around a defined customer journey. We can organise your approved business information, create language-specific instructions, add human escalation rules and test the system against realistic examples before connecting it to your website or customer channels.

The useful starting point is not “build an AI chatbot.” It is “which 30 customer questions should the system handle reliably, and which should it pass to a person?”

Book a free call at admov.io/#contact to plan the first language-quality sprint.