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Some Muslim-majority countries are investing in AI infrastructure, setting technology strategies, and building rules for digital assets. That is evidence of an effort to become technology producers—not proof that they have already done so. The clearest way to assess the race is to distinguish adopting technology from developing it locally, commercializing it, and exporting products or expertise.

What does it mean to be a technology producer?

Buying or using AI systems is not the same as producing them. A country can adopt advanced tools while relying on foreign models, cloud providers, software, and expertise. Production is better understood as a progression:

  1. Adoption: Public agencies and businesses use technologies developed elsewhere.
  2. Local capability: The country develops talent, research, data resources, computing infrastructure, and rules that enable domestic work.
  3. Development and commercialization: Local institutions and companies build systems or products and find customers for them.
  4. Export: Products, services, or expertise developed locally compete in international markets.

A national strategy or a large transaction figure can signal activity at one point in this progression, but it does not establish success at every later stage. The available examples show different kinds of institutional activity; they do not offer a comparable measure of locally owned products, export revenue, model performance, computing capacity, or value added across countries.

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Are Muslim-majority countries building their own AI?

There is no single policy bloc or shared result to describe. Saudi Arabia has set out a national AI ambition; Gulf Cooperation Council (GCC) governments are investing in infrastructure and publishing research; Indonesia is working to map local technology activity. These examples establish direction and activity, not a region-wide verdict on how much AI is being developed domestically.

Saudi Arabia: an explicit path from enablement to exports

Saudi Arabia’s National Strategy for Data & AI, approved on July 17, 2020, describes a staged ambition: act as a national enabler in 2021, become a specialist in 2025, and reach industry-leader status by 2030. Its stated goal is to compete internationally as an economy that uses and exports data and AI. Those dates and stages are strategy milestones and goals, not evidence in themselves that the milestones have been achieved.

The strategy treats AI production as more than a matter of software. Its stated priorities include data, infrastructure, talent, research, innovation, governance, adoption, and commercialization. SDAIA’s description of its 2024 State of AI in Saudi Arabia report likewise organizes the subject around seven pillars: policies and regulations, investment, infrastructure, data, talent and human capabilities, research and innovation, and adoption. Taken together, these priorities point to the kinds of capabilities that must connect for local research to become useful products.

A Saudi government portal also describes an ecosystem involving the Saudi Data and Artificial Intelligence Authority (SDAIA), the National Center for Artificial Intelligence, HUMAIN, Arabic-language large language models, data centers, cloud computing, and a Saudi Central Bank (SAMA) sandbox for testing financial digital solutions. These are official-page descriptions of institutions and activity; they do not, on their own, establish the scale, performance, domestic ownership, or export success of the resulting systems.

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GCC countries: investment and research, with outcomes still to measure

An International Monetary Fund (IMF) policy discussion in 2025 describes GCC governments as pursuing national AI strategies and investing in infrastructure such as supercomputers and data centers. It reports nearly 1,000 AI publications from GCC countries in 2023 and a 3 percent share of global AI publications in the first half of 2025. These publication figures indicate research output, not necessarily locally developed commercial systems, and they cover different periods. The figures should not be read as a direct measure of products or exports.

The same IMF discussion cites an estimate that AI adoption could raise Saudi labor productivity by about 5 percent more in the medium term under conservative assumptions. That is a conditional estimate, not a measured productivity increase or a forecast that applies automatically to every sector. The available discussion does not provide enough methodological detail here to treat the publication and productivity figures as a consistent cross-country scorecard.

Indonesia: trying to establish what the ecosystem contains

Indonesia’s Ministry of Communication and Digital sought public input on a draft annual report intended to map activity in AI, blockchain, and the Internet of Things. The proposed coverage includes business activity; technologies and infrastructure used or developed; adoption statistics; governance; data and datasets; and products or solutions. The initiative is evidence of an effort to measure the ecosystem. It is not, by itself, evidence of the ecosystem’s size, maturity, or ability to export.

What would show that AI investment is turning into production?

Announcements about strategies, facilities, or research matter, but they answer different questions from whether a country is building products that customers use. A useful assessment separates the evidence into several dimensions:

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  • Talent and research: Are local researchers and engineers producing work, and are those capabilities sustained in domestic institutions and companies?
  • Compute, data, and cloud: Is infrastructure available for local development, and who owns, operates, and controls access to it?
  • Domestic products and firms: Are local organizations developing systems, or mainly deploying products built elsewhere? Are there identifiable customers and recurring uses?
  • Capital and procurement: Do investment and public purchasing help local firms develop and scale products, rather than only fund infrastructure or deployments?
  • Commercialization and exports: Are locally developed products earning revenue, serving customers beyond the home market, or exporting technical expertise?
  • Governance: Are rules and oversight clear enough to support responsible development and use?

The cited national strategies and ecosystem descriptions speak to some of these conditions, particularly infrastructure, talent, research, governance, and adoption. They do not supply comparable evidence on domestic ownership, recurring commercial use, export revenue, or the share of systems built locally. Without those measures, claims that a country has become a technology producer should be treated as ambitions or partial indicators rather than a demonstrated end state.

Does crypto activity mean a country is producing technology?

No. Crypto transaction volume, investment interest, or a favorable regulatory stance can indicate activity in digital-asset markets; none alone shows that locally developed technology, companies, or intellectual property are creating durable economic value.

A UAE Government Media Office announcement about DMCC’s report, Digital Decentralisation: Crypto, DeFi and the Metaverse, says the UAE recorded USD 25 billion in crypto transactions in 2022 and was seeking to attract further investment through its regulatory stance. The figure is a 2022 transaction value reported by the study as relayed in the announcement. It is not a measure of UAE-built crypto products, investment raised, local value added, or export earnings.

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Why does crypto regulation matter to technology development?

Building a digital-asset industry requires more than attracting activity: authorities also need rules that can be implemented across borders and enforced in practice. In its October 22, 2024 status report, the Financial Stability Board (FSB) said nearly all FSB member jurisdictions had plans to develop or revise crypto-asset and stablecoin frameworks, or already had frameworks in place.

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The FSB also identified implementation gaps. Inconsistent rules can weaken the overall framework and encourage regulatory arbitrage; offshore cross-border activity and non-compliance make supervision harder. Stablecoins warrant particular attention because a loss of confidence can trigger runs on issuers or reserve assets. These are industry-wide regulatory concerns in the FSB’s report, not statistics specific to Muslim-majority countries.

For a country seeking to develop domestic firms, the practical question is not simply whether a regulation exists. It is whether rules are clear, coherent, and enforceable, and whether they give businesses a workable path to operate without leaving serious risks unaddressed.

What can—and cannot—be concluded about the race?

Saudi Arabia’s strategy sets out a clear progression toward international competition and exports. GCC governments are pursuing AI strategies and infrastructure investment, while the IMF figures offer indicators of research activity and a conditional productivity estimate. The UAE example documents reported crypto transactions and an effort to attract investment. Indonesia’s proposed report shows an attempt to measure a wider technology ecosystem.

Those are different forms of evidence, and none is a substitute for consistent measures of locally developed products, domestic ownership, commercial adoption, exports, and value created. The countries described are pursuing distinct approaches; the evidence does not support treating them—or Muslim-majority countries more broadly—as a single technology policy project. The strongest test of producer status is whether local capabilities lead to products and expertise that customers use, and whether those offerings can compete beyond the domestic market.

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