Insights · 7 min read

Arabic Business Data Value for AI Training: Why It Is Scarce

Scarcity helps value. Cleaning, dialect and rights decide how much of it you keep.

Bearish AI · October 21, 2026

If your company works in Arabic, your records may be rarer than similar English ones. That does not guarantee a price. We found no public price list for Arabic business data, and we would not trust one. What we can do is show, with sources, why Arabic data is scarce, where it is weak, and what makes a collection of Arabic work records more or less useful.

How thin is Arabic online?

Common Crawl’s language statistics for its crawl labeled CC-MAIN-2026-43 give Arabic about 0.67 percent of pages and English about 42.6 percent, using one language detector on each page’s primary language. CulturaX, a 6.3 trillion token multilingual dataset, lists Arabic at about 69 billion tokens, 1.10 percent, against English at 45.13 percent. These are measures of web text, not of business records, but they show the starting gap.

Translation is the usual workaround, and it falls short

The authors of the 101 Billion Arabic Words dataset cite the scarcity of original quality Arabic linguistic data and note potential bias from reliance on English datasets translated into Arabic. The Open Arabic LLM Leaderboard v2 dropped machine-translated tasks, citing their lower quality and possible cultural bias. The only Arabic code benchmark we found, 3LM, was built by translating two widely used code benchmarks, and its authors say existing Arabic benchmarks leave a significant gap in STEM and code.

Reading these together: researchers are moving toward native Arabic and human-translated material. Authentic Arabic business records written by working people are native by definition. That is an advantage, provided they are clean and lawful to use.

Dialect is where the difficulty lives

A 2025 benchmark tested 19 open models across English, Modern Standard Arabic and five dialects. Average accuracy was 62.8 percent in English, 51.9 percent in Modern Standard Arabic and 47.7 percent across the dialects, with Moroccan lowest at 45.0 percent, and the pattern held across the models tested. The models were open-weight ones of 1 to 13 billion parameters, so the paper says nothing about larger closed systems.

Dialect also complicates labeling. The ACL 2024 study of 15 multi-dialect datasets found strong support in 11 for a pattern: the more dialectal a sentence, the harder annotators find it to agree on labels, especially when they do not speak that dialect. Its authors recommend routing such samples to native speakers. For a data owner, that means real conversational work in a specific dialect has value, and that checking it takes the right people.

Recent research is also building dialectal data on purpose. Alexandria, accepted at ACL 2026, collects 107,000 conversational turns across 13 Arab countries and 11 domains, tagged by city of origin. That shows researchers want exactly this kind of locally rooted language. It does not show that anyone will pay a particular price for yours.

What makes Arabic business data more or less useful

Preparing an Arabic archive for review

• Identify the varieties in use. Note whether your staff write in Modern Standard Arabic, a Gulf, Egyptian or North African dialect, or mix Arabic and English in the same thread.
• Keep native reviewers in the loop. The ACL 2024 findings suggest dialect samples are best checked by speakers of that dialect.
• Do not translate to fill gaps. Machine translation is the habit research communities are moving away from, and it would erase what makes your records authentic.
• Remove personal data first. Names, phone numbers and account details appear in business chat constantly, in any language.
• Document the context. Which function, which years, which tools. It lets a buyer judge fit quickly.

The legal and practical limits

Saudi Arabia’s data protection law restricts transfers to countries without an adequacy decision, and SDAIA’s October 2026 draft amendments would add a duty to store personal data in the Kingdom and a registration requirement for controllers that transfer data abroad. They are drafts, not law. In the UAE, health data generally must stay in the country, and central bank rules require customer and payment data to be stored there. Arabic business records often contain exactly this type of information, so legal review comes before any export. Local legal advice is essential; see /insights/ai-data-licensing-value-by-region.

There is also a quieter limit. Scarcity helps only if buyers want the type of work you have. We did not find a public buyer program or price benchmark for Arabic engineering or business conversations, so we cannot say what any given collection would fetch. Treat any promised multiple with suspicion, and be especially wary of anyone who quotes you a premium for Arabic without asking about dialect, years and rights.

How to place yours

Note which dialects and which mix of Arabic and English your people actually use, which functions the records cover, and how many years. Then run the free estimate at /estimate, which includes language as one of its inputs and stays conservative. Before sharing anything, remove personal data and check rights and local transfer rules with a lawyer. A small or messy archive is still worth little, in Arabic as in English.