Digital Sovereignty: Why the Arab World Needs Its Own AI Models

When you ask ChatGPT a question in Arabic, you get an acceptable answer. But try asking it for a religious ruling, drafting a contract under Tunisian law, or chatting in Gulf dialect — and you'll quickly realize these models weren't built for us.

This isn't just a technical flaw. It's a sovereignty gap.

What Does Digital Sovereignty Mean in the Age of AI?

Digital sovereignty refers to the ability of nations and societies to control their data, digital infrastructure, and the AI models that shape their decisions — without full dependence on external entities.

In 2026, this concept is no longer theoretical. Countries are now competing to build sovereign AI models trained on their own values, culture, and local languages. And the Arab world is entering this race with unprecedented seriousness.

Why? Because whoever owns the model owns the influence. And Western models — despite their technical superiority — carry cultural and linguistic biases that don't serve the 491 million Arabic speakers worldwide.

The Problem: Arabic Is Marginalized in the AI World

The numbers are stark:

• Only 0.5% of natural language processing (NLP) research focuses on Arabic
• Arabic encompasses over 30 dialects across 22 countries, making comprehension a unique challenge
• Most training data for major models comes from the English-language internet, where Arabic content represents a tiny fraction

This means global models:

• Fail to understand local dialects (Tunisian Darija, Saudi dialect, Egyptian Arabic)
• Don't account for the region's cultural and religious context
• Deliver less accurate results in Arabic legal, medical, and financial domains
• Lack a deep understanding of Arabic idiomatic expressions and rhetoric

The Arab Race: Who Is Building What?

Jais 2 (United Arab Emirates)

Inception (a G42 subsidiary), in collaboration with Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and Cerebras, launched Jais 2 with 70 billion parameters, trained on the largest Arabic dataset ever assembled — 600 billion Arabic tokens.

What makes Jais 2 stand out:

• Open-weight model — any organization can download, use, and customize it
• Advanced performance surpassing previous models that achieved around 62% on evaluation benchmarks
• Bilingual training (Arabic-English), making it effective in mixed-language contexts

ALLaM (Saudi Arabia)

The Saudi Data and AI Authority (SDAIA) developed ALLaM with exceptional specifications:

• Trained on 500 billion Arabic tokens — the largest Arabic dataset in the world at the time of its launch
• Built with contributions from 16 Saudi government entities
• Tested by over 400 specialized experts through more than one million trial conversations
• Explicitly integrates Islamic values and regional cultural context

HUMAIN Initiative (Saudi Arabia)

The Saudi Public Investment Fund (PIF) launched HUMAIN as a comprehensive platform for building local AI models serving 400 million Arabic speakers in the region. The goal: building sovereign infrastructure for Arabic AI.

Why Local Models Are a Necessity, Not a Luxury

1. Linguistic and Cultural Accuracy

Global models treat Arabic as a single language. But the difference between Modern Standard Arabic, Tunisian Darija, and Saudi dialect is larger than it appears. A locally trained model understands that "behi" means "good" in Tunisia, and that "ya zein" carries different meanings in Saudi Arabia versus Iraq.

2. Legal and Regulatory Compliance

Every Arab country has its own legal system. A model trained on Tunisian, Saudi, or Emirati law delivers far more accurate results than a general model that doesn't distinguish between different Arab legal frameworks.

3. Data Protection

When an Arab company uses a model hosted in the US or Europe, its data falls under those countries' laws. Local sovereign models ensure sensitive data stays within national borders.

4. Competitive Advantage

Companies building on local models gain a deeper understanding of their customers, more market-relevant products, and lower operating costs in the long run.

The Challenges: The Road Isn't Easy

Despite notable progress, building sovereign Arabic models faces real challenges:

Scarcity of high-quality Arabic data: Arabic content on the internet remains limited compared to English. Gathering diverse and accurate training data requires massive institutional effort — which is exactly what Saudi Arabia did by mobilizing 16 government entities.

Specialized talent: Developing large language models requires rare expertise in AI engineering. The region is investing in building these capabilities — MBZUAI alone has certified over 32,000 experts.

Cost: Training a 70-billion-parameter model demands enormous computing infrastructure. That's why we see strategic partnerships with companies like Cerebras to provide the necessary computational power.

Standardization vs. diversity: Should we build one unified Arabic model or specialized models for each country? The emerging answer is layers: a broad foundational model, followed by precise fine-tuning for each market.

What This Means for Businesses in the Region

If you're running a business in the Arab world, here's what you need to know:

The opportunity is here now: Jais 2 is open-source and available for commercial use. You can customize it for your sector and your customers' language without waiting.

Don't rely on a single solution: Use global models where they excel (coding, technical analysis), and local models where they shine (Arabic customer service, cultural content, legal compliance).

Invest in your data: The most valuable asset your company owns today is its data. Organize it, clean it, and store it in a way that allows training custom models on it in the future.

Start experimenting: You don't need a massive budget to begin. Try Jais 2 on a specific use case — customer service, content classification, document summarization — and measure the results.

Looking Ahead

2026 is the year the Arab AI world transitions from consumption to production. The region is no longer just a user of Western technology — it has become a producer of its own.

With investments exceeding $100 billion in AI infrastructure between the UAE and Saudi Arabia, and with open-source models like Jais 2 enabling everyone to build upon them, we're witnessing a pivotal moment.

The question is no longer "Do we need Arabic AI?" — it's "How do we leverage it before our competitors do?"

Looking to integrate Arabic AI models into your business? Contact Noqta to explore the right solutions for your needs.