Equatorial Guinea
GDP per capita to 2060, by scenario
Constant-rate scenario path; the 2060 endpoint levels are illustrative, not forecasts.
Factor profile
Military governments, very weak state capacity, or limited access to the AI supply chain keep these countries from converting AI into growth.
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
Production is relatively manufacturing-intensive. Near-term effects depend on machinery, robotics, supply chains, energy and firms’ capacity to reorganize production, as well as on language models.
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 Equatorial Guinea starts
Equatorial Guinea enters the AGI era in the high-risk, volatile group: countries cut off from the AI supply chain, or whose state capacity is too weak to turn AI into growth. The scores show the split. Language inclusion is 4.6, demographics 4.5 and climate resilience 4.5, all high. But compute and energy access is the lowest possible at 1, physical build speed 1.2, cyber resilience 1.2 and AI diffusion 1.5. This is an oil economy. Crude from the Zafiro, Ceiba and Alba fields and the Punta Europa LNG plant built the state, and their decline explains a ten-year trend growth of -4.3% a year. At about $6,615 GDP per person, income is middle-ranking but shrinking. The new administrative capital, Ciudad de la Paz, shows the ambition; the missing power grid and thin digital base show the constraint.
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. Equatorial Guinea would keep shrinking, at -4.2% growth a year, ranked 157th of 157 — last in the world, as the oil runs down. Under Gradual takeoff, growth would climb over two decades and reach 3.1% a year once AGI matures around 2045, lifting the country to 146th. That turns decline into slow growth. An economy growing at 3.1% doubles in about 23 years. Under Fast takeoff, growth would reach 2.8% a year from the early 2030s, ranked 149th, a doubling roughly every 25 years. Notice the order: this is one of the few countries that would do slightly better under a gradual takeoff than a fast one, because speed rewards the compute and capital it lacks most. Both AGI paths beat the oil decline, but neither is transformative. Regulation and politics could slow or redirect any path. How the population and its leaders respond to transformative AI is a variable the model holds constant.
How you would know which world you are in
The scenarios look almost the same until about 2030, so watch leading indicators, not GDP, and watch them live. 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. Equatorial Guinea's own signals would arrive earlier than the GDP data: whether oil and LNG revenues stabilize or keep falling, whether the electricity grid reaches beyond Malabo and Bata, and whether any credible fiber, data center or digital-government contract is signed at all.
If growth goes explosive
Explosive is the wrong word here, and honesty demands saying so. At 3.1% growth a year under the gradual path, Equatorial Guinea would trail the frontier badly, where the United States would compound at nearly 20%. It would also sit below the Sub-Saharan median of 5.7%. What both AGI paths do is stop the bleeding: they turn an oil-driven decline into modest growth. The economy would double in a little over two decades, not a few years. The population is small, under two million, and young, so labor demand would firm and the pull to emigrate for work would ease somewhat. There is a real way AGI leaves the country worse off. Its budget rides on oil and LNG. A fast, AI-driven energy transition could cut global demand for both, draining the revenue that funds the state before any new industry replaces it. The hedge is to convert oil rents now into power, skills and digital infrastructure while the money still flows. Even in the better scenarios, the pressure would land on the oil ministry, the weak non-oil tax base and courts that have never had to permit or adjudicate at speed.
What Equatorial Guinea can do now
Three levers follow from the scores, and two pay off whether or not AGI arrives. The first no-regret move is AI diffusion capacity, at 1.5. Digital skills, permissive rules for deploying technology and digitizing government services would raise productivity in any world; a cautious government can start today and lose nothing. The second no-regret move is physical build speed, at 1.2. Statutory time limits on permits, one-stop approvals and pre-zoned land with transmission built ahead of demand would help every project, oil or otherwise. The third lever is the bet. Compute and energy access, the lowest score at 1, barely moves growth if AI stays ordinary, but under a fast takeoff it becomes the single biggest lever, carrying more weight than any other factor. Its energy half is worth doing regardless: a grid that reaches beyond Malabo is basic development. Equatorial Guinea can borrow from a peer — DR Congo is pushing large-scale hydropower at Inga to turn a resource into exportable electricity. Open the atlas's policy editor to see how raising these scores shifts the country's path under each scenario.
Use the policy editor to test how different factor scores change Equatorial Guinea’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 Equatorial Guinea: 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.