AI in the Middle East: what will the business models be?
AI is no longer a nice-to-have. If your country (or region) doesn’t build AI, it means you’re depending on someone else for today’s most important technology. It’s why the French government features Mistral in its official video":
Of course, we all know about the big U.S. AI labs: Anthropic, OpenAI, Meta, Google… but one region that’s betting big on AI is the Middle East.
Not too long ago, Ben Horowitz, Sam Altman and Elon Musk went to Abu Dhabi. The result? The Stargate UAE project, a major AI compute cluster under OpenAI’s Stargate project.
The unveiling has put the UAE on the map, but it’s not the first time Middle Eastern countries invest in AI projects. We dove into Middle Eastern AI projects and the quiet advances the region has made.
A constellation forming beyond Stargate
Stargate is only one of many AI initiatives in the Gulf. Abu Dhabi has already launched AI71, a venture-backed outlet that hardens the open-sourced Falcon models into “air-gapped” packages for clients in health care, finance and defense. Its public calls for proposals bundle free compute credits with Emirati-hosted weights.
Over the water in Riyadh, the Public Investment Fund introduced HumAIn in May. Chaired by Crown Prince Mohammed bin Salman, the new company pledges to build Arabic multimodal models, aggregate data-centre projects and steer as much as US $10 billion of fresh capital toward local founders.
Saudi Arabia has also recently given Groq a $1.5b commitment for expanded delivery of its infrastructure.
The region is also importing talent: a Paris press conference in late May unveiled a strategic partnership between G42 and Mistral AI to co-design next-generation foundation models and the infrastructure needed to run them at scale.
Additionally, the UAE is giving everyone in the country free access to ChatGPT Plus, which is OpenAI’s $20 plan.
Now, why do all of this? Why not just sit, watch and buy the tools when they’re ready? First, Middle Eastern states have long tried to transition away from its oil riches. Second, energy is scarce in some places, but many Middle Eastern countries have abundant solar and nuclear energy. Third, AI sovereignty is a real concern.
When compliance becomes a feature, not a hurdle
Saudi Arabia’s Personal Data Protection Law came into force in 2023 and became fully enforceable on 14 September 2024, ending the grace period regulators had granted companies to localise personal data. This makes it harder to use digital services (including AI) from outside the country. A third round of amendments to the implementing regulations closed in April 2025, signalling that the rule-set will only tighten. Similar drafts are under way in the UAE and Qatar.
If the region wants to be important to the technology of the future without losing sovereignty, they’re doing it just right.
That shift turns sovereignty into a billable line-item. It creates real business incentives to build AI in the Middle East, especially for big enterprises, banks and ministries.
Are AI economics better in the Middle East?
Running sovereign LLMs is brutally capital-intensive. Depreciation alone on an eight-GPU H100 tray (priced north of US $150 000) creates a floor cost for every million tokens. Cooling those chips through a Gulf summer costs even more opex. If vendors don’t charge for their costs downstream, margin evaporates.
Business model choices matter too: the Apache-2 licence Falcon uses is fantastic for adoption, but pushes revenues toward hosting. Watad’s decision to keep Mulhem’s weights private leaves room for per-cluster fees.
How the money wants to flow
Capital is available, both from governments as well as private initiatives. Regional AI start-ups are growing massively, while U.S.-based companies like OpenAI are expanding into the region. Humain is reportedly exploring an AI fund of $10 billion. Investors backing those numbers are expecting a return.
AI in the Middle East—what will the business models be?
Public endpoints will still charge per token—it remains the simplest mental model for developers—but the real money is likely to come from three additional levers.
First, managed fine-tunes priced by GPU-hour let enterprises customise a base model without dealing with drivers, vapour chambers or firmware updates. Second, private-cloud licences fold compute, storage and support into a single, high-ACV contract that satisfies auditors in one stroke. Third, compliance toggles—a “PDPL (personal data protection law)-only” mode or an “air-gapped” setting—add a surcharge to every regulated request.
To make those levers profitable, billing needs the same flexibility the models promise. A platform like Lago, which decouples what you meter from how you price, lets a founder ship a GPU-hour SKU today and a Saudi-only token SKU tomorrow without digging back into inference code.
What early movers are doing
AI71 has already adopted the Red Hat playbook: the Falcon weights remain free, but the air-gapped deployments and 24-hour SLA cost real dirhams. G42 and Mistral say their first joint offering will marry multilingual agent tooling with an elastic infrastructure layer. We expect usage fees to track tool calls and latency budgets rather than raw tokens.
HumAIn’s mandate runs end-to-end, which means rack space to benchmark to business model. Insiders talk about bundling compute and model access into a sovereign cloud product pitched somewhere between AWS GovCloud and a traditional on-prem licence.
The take-away
The Gulf is starting to rival far bigger regions in its AI potency. With policy momentum on its side and tech-friendly governments, it’s starting to look like a matter of time before the first major AI player is located in the UAE. But GPUs alone do not create durable businesses. The winners will be teams that treat pricing as product, compliance as feature and billing as infrastructure. If you’re juggling tokens, GPU hours and on-prem licences, grab Lago’s open-source stack and start experimenting—then let the rest of us know what you decide to meter next. In the desert, as in the cloud, margin favours those who master the hidden costs.