Mauritania
GDP per capita to 2060, by scenario
Constant-rate scenario path; the 2060 endpoint levels are illustrative, not forecasts.
Factor profile
These economies supply copper, fuels, bauxite, iron ore, uranium and other inputs required for the build-out.
How this economy meets AI
Today’s production, workforce and automation baseline — context for the scenarios, outside the AGI Growth Index.
Where output comes from (% of GDP)
Where people work (% of employment)
Informal employment
Current automation exposure
Several parts of the economy could transmit AI’s effects. The pace depends on adoption by firms, connectivity and movement of workers between sectors.
This country is not covered by the Global Automation Atlas’s public country file; its task-level exposure work for other countries is at automationatlas.org.
Sources: World Bank WDI; ILOSTAT; Global Automation Atlas (Garg, Crosta & Baier, 2026). The latest available year is shown for each measure; vintages differ, so shares may not sum to 100.
Where Mauritania starts
Mauritania enters the AGI era as a resource supplier: a country that sells the build-out its raw inputs. Iron ore is about 38% of its exports, shipped from Nouadhibou by the state miner SNIM. The scores explain the archetype. Catch-up headroom is 3.9 out of 5, high, because Mauritania starts far behind and has room to converge. But the inputs a modern economy needs are thin. Compute and energy access score 1, the lowest band. AI diffusion capacity is 1.2, and climate resilience is 1.2. New offshore gas from the Grand Tortue Ahmeyim field, shared with Senegal, and large green-hydrogen plans give it fresh energy assets. At about $2,198 a person, Mauritania is lower-middle-income. Ten-year trend growth is 4.1% a year.
The three paths
These are simulations, not forecasts. The Modest path is the baseline, and the two AGI scenarios fork from it. Under the Modest scenario, AI stays a normal technology. Mauritania would hold its trend: 4.1% growth a year, 42nd of 157. Its commodity exports would carry the economy much as they do now. An economy growing at 4.1% doubles in about seventeen years. Under Gradual takeoff, growth would edge up to 4.4% a year once AGI matures around 2045, after a two-decade ramp. Yet its rank would fall to 135th, because the frontier races ahead while Mauritania barely moves. Under Fast takeoff, growth would reach only 3.6% a year from the early 2030s — slower than the 4.1% it would have managed without AGI at all. Its rank would slip to 140th. A fast world rewards compute, capital and geopolitical weight, the very assets Mauritania lacks, so it loses ground even as demand for its ore rises. Politics could slow or redirect any of these paths. How Mauritanians and their government respond to transformative AI is a variable the model holds constant.
How you would know which world you are in
The scenarios look almost identical until about 2030. In all three, the late 2020s add only fractions of a point to growth. So watch leading indicators, not GDP, and check them live rather than trust any snapshot. Three global signals matter most. First, whether the METR task horizon curve keeps doubling every four to five months through 2027–28; METR publishes it at metr.org. Second, whether frontier lab revenue and capital spending keep compounding; Epoch AI tracks both at epoch.ai. Third, whether growth in the ten to twenty most-ready economies — the United States and China above all — breaks above trend in the early 2030s. Double-digit growth there within a couple of years of 2030 would signal a fast world. A point or two above trend by the mid-2030s would signal a gradual one. A fade back to trend would signal a modest one. Mauritania's own signals would arrive earlier than GDP data: SNIM's iron ore order books and prices, gas shipments from Grand Tortue Ahmeyim, and financial close on its green-hydrogen projects.
If growth goes explosive
Explosive is the wrong word for Mauritania's numbers. Even under Fast takeoff its growth would be 3.6% a year, below its own recent trend and far below a frontier compounding at more than 39% a year. This is relative decline, not a boom. The economy would still double, but slowly, over about twenty years. Mauritania has one of the world's youngest and fastest-growing workforces. Faster domestic growth would raise labor demand and wages, which eases the pressure to emigrate for work. The honest downside is written into the data. Under Fast takeoff Mauritania would grow more slowly than without AGI, because rising ore demand cannot offset how far its compute, capital and connectivity gaps hold it back. A commodity windfall is not a development strategy; rents that are not converted into grids, schools and firms simply evaporate. The hedge is to save and reinvest the windfall while it lasts. Even a windfall would test the state: SNIM's governance, the ministries in Nouakchott that permit and count, and the fund meant to hold resource revenue.
What Mauritania can do now
Three levers follow from the scores, and two pay off whether or not AGI arrives. The first is AI diffusion capacity, low at 1.2. Digital skills, permissive rules for deploying technology, and digitizing government services carry real weight even in the skeptic's world, so this is a no-regret move. Start by putting basic services online and training officials to use them. The second no-regret lever is physical build speed, at 2. Faster permitting, pre-zoned industrial land, and transmission built ahead of demand pay off under every scenario, and would extend electricity to Mauritanians who still lack it. The third lever is the bet. Compute and energy access, at 1, is the highest-weight factor under Fast takeoff but barely moves growth if AI stays ordinary. Closing it means packaging Mauritania's solar and wind power with land and fast permits to draw investment. Chile shows the model: its national green-hydrogen strategy is turning a renewable endowment into an exportable energy business. A cautious government can act on the two no-regret levers today and lose nothing if the skeptics prove right. To see how moving these scores changes Mauritania's path, open the atlas's policy editor.
Use the policy editor to test how different factor scores change Mauritania’s modeled path. The roadmap builder below can then incorporate those targets into a 1,000-day planning prompt.
Drafted with Claude, Anthropic’s AI model, from the atlas’s data and an editorial template set by the author.
Create a 1000-day AGI and growth roadmap prompt
This prompt can be used with Claude, ChatGPT or an open-weight model hosted on your institution’s systems. It includes the atlas material for Mauritania: the country brief, economic structure, region, archetype and global scenarios. It instructs the model to ask for local information, use existing strategies and the political calendar, and preserve the atlas’s interpretation rules. The prompt is assembled in your browser; the information entered here is not sent elsewhere.
1 · Read the brief → 2 · Set targets in the policy editor → 3 · Generate and copy the prompt → 4 · Run it with an approved model, with high reasoning effort and web access where permitted
Instructions are generated in the selected language; the data annex remains in English. Translations are machine-drafted, and corrections from native speakers are welcome through the contact links on the start page.