Guyana
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
Production and exports are resource-led. Direct workplace exposure may be limited, while global demand, commodity prices, extraction productivity and ownership of the resulting capital still transmit AI’s effects.
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 Guyana starts
Guyana enters the AGI era as a resource supplier — a country that sells the build-out its inputs. In Guyana's case that input is oil. Fuel is 86% of exports, pumped from the ExxonMobil-led Stabroek Block offshore. Two scores mark the country out. Compute and energy access is 1 out of 5: there is almost no data center capacity, and the grid is only now being expanded through the Gas-to-Energy project. Catch-up headroom is also 1, the sign of thin institutions and limited capacity to absorb new technology. Its strengths are milder: language inclusion at 3.1 and climate resilience at 3. At roughly $32,400 GDP per person, Guyana looks rich on paper, but the figure reflects oil, not a broad economy. Ten-year trend growth of 4.5% uses the IMF's medium-term view; the oil startup distorts the raw average.
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. Guyana would hold its oil-driven pace: 4.5% growth a year, 36th of 157, an economy doubling in about 16 years. That rank is high because 4.5% is strong when the rest of the world is slow. Under Gradual takeoff, growth would rise only slightly, reaching 5.2% a year around 2045 after a two-decade ramp. But Guyana's rank would fall to 127th, because faster-moving economies would race past it. Under Fast takeoff, growth would reach 5.4% a year from the early 2030s, doubling roughly every 13 years — yet the rank would still sit at 116th. The pattern is the point: Guyana's growth barely changes across scenarios while the world around it speeds up. Its two weak spots, compute and thin absorptive capacity, keep it from catching the wave. Politics could slow or redirect any path. How Guyanese 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. 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. Guyana's own signals would arrive earlier than the growth data: the pace of ExxonMobil's production ramp, world oil prices and demand, financial close on the Gas-to-Energy plant, and whether AI-driven economies keep burning oil or electrify away from it.
If growth goes explosive
For Guyana it would not. By world standards its rates are modest: 5.4% under fast takeoff, against a frontier compounding at more than 39% and a Latin American median near 9%. Guyana would fall behind both. Measured against its own history, 4.5% is already brisk, and AGI adds little to it. The economy would keep doubling roughly every 13 years, still built on oil. Rising wages at home could ease the long-standing pressure to emigrate, though the model does not treat returning workers as a source of growth. Here is the honest risk. A commodity boom is not a development strategy. Oil rents can evaporate, and a world of cheap machine intelligence may burn less oil, not more. If Guyana banks the money without turning it into skills, firms and institutions, it drifts while the frontier races. The hedge is to spend the Natural Resource Fund on absorptive capacity. The test then falls on Georgetown's small civil service, its EPA permitting and the fund's own governance.
What Guyana can do now
Three levers follow from the scores, and two pay off whether or not AGI arrives. The first no-regret lever is catch-up headroom, the weakest score at 1. Stronger institutions, secure property rights and better schools raise growth in every scenario, and they are the classic cure for the resource curse. The second no-regret lever is AI diffusion, at 2.5: digital skills, permissive deployment and digitized government services help a slow world and a fast one alike. The third lever is the bet. Compute and energy access, at 1, barely moves growth if AI stays ordinary, but under fast takeoff it becomes the single biggest lever. Closing it means turning new gas-fired power and cheap land into packages that draw data center investment. Guyana can adapt a proven model from its own archetype: Chile turned copper rents into a structural fiscal rule and sovereign funds, then used stable power and institutions to attract real data center investment. A cautious government can act on the two no-regret levers today and lose nothing. Open the atlas's policy editor to see how moving these scores reshapes Guyana's path under each scenario.
Use the policy editor to test how different factor scores change Guyana’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 Guyana: 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.