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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →AI could raise productivity, support economic growth and help diversify economies across Africa, the Middle East and Türkiye—but the value will depend on whether countries can access the technology and put it to effective use. Exposure to AI, reliable infrastructure, skills, locally relevant data and capable institutions all affect who benefits. The available estimates are conditional scenarios, not guarantees or comparable forecasts for every country.
What does AI’s economic value depend on?
AI can contribute to economic value when people and organizations use it to do useful work more productively, develop new products and services, or improve how existing industries operate. But potential exposure to AI does not automatically translate into growth. The International Monetary Fund’s 2025 global analysis frames the outcome around exposure to AI, preparedness, and access to essential data and technology.
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That distinction matters across these three regions. Economies differ in the kinds of work and industries exposed to AI, their ability to adopt it, and who can access the necessary tools. A country’s potential gains also depend on whether workers, firms and public institutions can adapt—not simply on whether AI systems are available somewhere in the market.
What foundations make AI adoption possible?
The World Bank’s Digital Progress and Trends Report 2025: Strengthening AI Foundations identifies four practical areas for investment:
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- Connectivity: reliable internet access that lets people and organizations reach digital services.
- Compute: the processing capacity needed to develop or use AI systems.
- Context: relevant data that reflects local needs and circumstances.
- Competency: the skills people need to build, use and manage AI.
Compute access is a particular strategic choice: countries and institutions can invest in domestic capacity or rely on services delivered through international cloud infrastructure. The World Bank describes compute as “the new electricity in the AI era—essential but unevenly distributed.” Access alone, however, does not ensure that AI systems are appropriate for local languages, industries or public needs; relevant data and human expertise also matter.
How can AI boost productivity in Sub-Saharan Africa?
The IMF’s 2026 analysis focuses on Sub-Saharan Africa, not the whole African continent. It identifies a central challenge: whether countries can adopt, adapt and scale AI quickly enough to capture its potential benefits. The report points to unreliable or insufficient electricity, limited digital infrastructure, scarce technical skills, and gaps in regulatory and institutional capacity as constraints.
The IMF’s executive summary gives a conditional scenario range for the next decade. These figures describe modeled possibilities dependent on policy choices and AI’s eventual economic effect; they are not observed gains or guarantees for individual countries.
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| IMF Sub-Saharan Africa scenario, 2026 | Modeled possibility | How to interpret it |
|---|---|---|
| Productivity over the next decade | Potential increase of 0.2% to 2.1% | A conditional range, not a realized result or a prediction for every country. |
| Annual GDP growth over the same period | Nearly 0.5 percentage point in the upper-potential scenario | A possible result at the upper end, not an unconditional regional forecast. |
| Cumulative GDP effect | About 4% in the upper-potential scenario | A scenario outcome over the stated period, not a guaranteed gain. |
The range signals how much the outcome depends on adoption and policy rather than establishing a single expected result. Infrastructure, skills and institutional capacity affect whether potential applications can move beyond limited use and scale across firms and services.
How might Middle Eastern economies benefit?
The IMF’s 2026 regional analysis covers the Middle East and North Africa, Afghanistan and Pakistan (MENAP), as well as the Caucasus and Central Asia. That grouping is broader than the Middle East alone, so its findings should not be presented as forecasts for every Middle Eastern country.
The IMF identifies potential for AI to raise productivity, strengthen medium-term growth and support economic diversification across the covered economies. It also emphasizes that outcomes will differ with exposure, preparedness and access to advanced technologies. Economies with stronger infrastructure, skills and institutions can focus on innovation ecosystems and adapting legal and regulatory frameworks. Less-prepared economies have more foundational needs, including digital infrastructure and human capital.
What is distinctive about Türkiye’s opportunity?
The OECD’s Economic Survey of Türkiye 2025 treats productivity as increasingly important to future growth. Its proposed strategy is to encourage innovation and new-technology adoption, improve workforce skills, and reduce barriers to business dynamism, including through trade openness. This is an economic strategy for technology adoption broadly; the survey’s figures do not measure AI’s contribution.
Two indicators provide context, but neither is an AI-adoption measure:
- Türkiye’s share of medium-high-technology exports rose from 32.2% in 2015 to 37.5% in 2024, according to the OECD’s 2025 survey. This indicates industrial upgrading, not proof of AI use.
- OECD data for 2012–2022 show annual labor-productivity growth of 3.1% nationally in Türkiye, compared with 0.9% across OECD regions. These are productivity figures, not estimates of AI-caused growth.
National averages also conceal meaningful differences within Türkiye. Over 2012–2022, the OECD recorded annual labor-productivity growth of 4.7% in Southern Aegean and Western Black Sea – West, while Southeastern Anatolia – Middle recorded -0.1%. These regional results describe labor productivity, not the effects of AI.
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There is no basis here for ranking countries by AI readiness or forecasting their economic returns on a comparable country-by-country scale. The IMF’s 2025 global model estimates that the growth impact in advanced economies could be more than double the impact in low-income countries. This is a modeled global comparison, not a measurement for Africa, the Middle East or Türkiye. The IMF also finds that improvements in preparedness and access can mitigate some of the disparity.
Usage figures offer a separate illustration of unequal access, but they must not be mistaken for regional adoption rates. The World Bank’s 2025 report estimates that ChatGPT was used in April 2025 by 5.8% of internet users in upper-middle-income countries, 4.7% in lower-middle-income countries and 0.7% in low-income countries. These are income-group figures, not rates for Africa, the Middle East or Türkiye, and they measure use of one service rather than AI’s broader economic effect.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallFor decision-makers, the implication is to ask not only whether AI is being adopted, but where its benefits accrue: across countries, firms, workers and regions. Adoption that is concentrated among a small number of organizations or locations may not translate into broadly shared productivity gains.
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What can the evidence establish—and what can’t it?
The cited reports support a case for AI’s potential economic value, alongside a clear account of the foundations and policy choices that shape it. They do not establish realized AI-driven growth across these regions, nor do they provide comparable current estimates of AI adoption and economic effects for individual countries throughout North Africa and the Middle East. Türkiye’s productivity and export indicators are useful economic context, but they are not measurements of AI’s impact.
The strongest way to read the evidence is therefore as a conditional opportunity: productivity and diversification may improve where infrastructure, compute, data, skills and institutions enable useful adoption. The scale and distribution of gains remain dependent on local circumstances and choices.
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