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AI adoption in the GCC: what the numbers miss

Personal use in the region is among the highest measured anywhere. Business adoption is not. On the gap between the two, and what sits in it.

There is a number about the UAE that gets quoted constantly and is worth quoting accurately, because the accurate version is more interesting than the version in circulation.

64.0%
of the working-age population used generative AI, the highest rate of any economy measured.H2 2025 · Microsoft AI Economy Institute
16.3%
the global average on the same measure, across roughly 150 economies.H2 2025 · Microsoft AI Economy Institute

Close to four times the global rate. Whatever else is true about this market, the population is not waiting to be convinced. Your staff are using these tools. So are your customers, and so are your competitors' staff.

The measure that is not being taken

Here is the part that gets left out. That figure measures people, not businesses. It counts the working-age population of a country using a generative AI product for any reason, including a student and a person planning a holiday.

The equivalent business measure exists in the UK, in Canada, in the United States and in Saudi Arabia, because those countries' statistics offices ask about it. The United Arab Emirates publishes no comparable national statistic on business AI adoption. Neither does South Africa. What circulates in their place is vendor research, which is not the same instrument and is not held to the same standard.

A market can be the most AI-saturated consumer economy on earth and have no published idea what its businesses are doing.

Saudi Arabia is the exception in the region and is worth watching precisely because it measures itself.

33.1%
of establishments used AI technologies, a rise of 20.0% in one year.2025 · GASTAT, Establishments' ICT Access and Usage Statistics
26.2%
of the Saudi working-age population used generative AI.H2 2025 · Microsoft AI Economy Institute

Saudi Arabia is one of very few markets anywhere where the business figure sits above the personal one. Read that against the UAE, where personal use is the highest measured on earth and the business figure does not exist, and the two neighbours are running different experiments.

What the gap means if you operate here

In a market where two thirds of the working-age population already use these tools, the question facing a business is not whether AI arrives. It has arrived, on personal accounts, without a policy, without a procurement process and without anyone deciding what data is allowed to leave the building.

That produces a specific and slightly uncomfortable situation. The organisation has adopted AI. It has not decided anything about it. Every choice that would normally be made deliberately, about which tools, which data, what gets checked and by whom, has been made by default, one person at a time, and nobody has written any of it down.

  • It is already happening, so a policy of not yet is not available. The available choice is between deliberate and accidental.
  • There is no local benchmark to hide behind. In the UK a business can ask how it compares to the published 35%. Here there is no number, so the comparison has to be against your own last quarter.
  • The talent assumption is different. In markets where personal use is low, adoption starts with training. Here it does not. The constraint is structural, not educational.

What would actually be worth measuring

If the UAE published one business statistic, the useful one is not the share of businesses using AI. It is the share that have changed a process because of it. Those are very different questions, and the first one is already close to answered by watching what people do on their phones.

Until that exists, the honest position is the one this page takes elsewhere: where a market publishes a figure it is quoted with its source, and where it does not, we say so rather than substituting one from a vendor deck. A market with no data is not a market with good news.

New writing, when there is some

A short note when something is published: what it is about and a link. No more than a couple a month, and nothing else.

Start with
the diagnostic.

A scoping conversation costs nothing and ends with a straight answer about whether there is enough here to be worth doing. If there is not, we will tell you.

Questions. Asked before every engagement.

Your data is yours. You can export it at any time, and it is exported to you in a documented format before any engagement closes. The software itself is licensed: we build it around your business, host it, and run it, and you pay monthly for that. If you'd rather own it outright, that's possible. It's a different kind of engagement and it's priced accordingly. Licensing keeps maintenance our problem rather than yours, which is why it is the default.

Two weeks' notice, either side. Your data is yours. You can export it at any time, and it is exported to you in a documented format before any engagement closes. The system stops running. If you'd rather keep it running, the ownership option is available at that point as well. Ending the retainer doesn't force you to lose what was built.

Typically four to eight weeks from signing to a working system, depending on how many tools it connects to and what state the data is in. A scoping conversation and a written plan come first, so the timeline is agreed before anything is committed to.

Access to the tools and data the system will work with, one person who can make decisions, and a few hours in the first two weeks while we map how work actually moves through your business. After that, very little. The point of the engagement is that it runs without your attention.

Usually. Most business software exposes an interface we can build against, and where one doesn't there's normally a way around it. Which connections are viable is settled in the scoping conversation, so you find out before committing rather than after.

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That's the normal starting point, and mapping them is part of the work. Automating a process nobody has examined just makes the confusion faster, so we don't start there. The first phase establishes how things actually happen, as opposed to how they're supposed to.