Guatemala
GDP per capita to 2060, by scenario
Constant-rate scenario path; the 2060 endpoint levels are illustrative, not forecasts.
Factor profile
They earn from what cannot be sent down a wire: visitors who come, and workers abroad who send money home.
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
The economy has a meaningful exposed segment, while much of the informal workforce may capture productivity gains more slowly. Disruption could therefore precede widespread benefits.
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 Guatemala starts
Guatemala enters the AGI era as a stalled middle economy: middling income, middling scores, slow growth. The label fits the numbers. Its distinguishing strengths are people and language. Demographics and migration score 4.1, among the highest in its group, and Spanish-language inclusion scores 3.9. A young workforce and a widely spoken language are real assets. What holds it back is capacity. Compute and energy access scores 1.1, AI diffusion 1.8, cyber resilience 1.5 — near the bottom on all three. The economy runs on remittances from the United States, on coffee and cardamom exports, and on maquila textiles sold north. It also sells power to neighbors through the SIEPAC grid. Ten-year trend growth is 3.5% a year, and at about $6,598 per person Guatemala is lower-middle-income. The gap to faster economies widens each 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. Guatemala would edge just above trend: 3.6% growth a year, 53rd of 157. That is close to its own history, driven by the same mix of remittances, farming and light manufacturing. Under Gradual takeoff, growth would climb over two decades and reach 6.1% a year only around 2045. Yet its rank would fall to 110th, because faster economies pull away. An economy growing at 6.1% doubles in under twelve years. Under Fast takeoff, growth would arrive from the early 2030s and settle at the same 6.1% a year, ranking 106th. The two AGI paths deliver near-identical rates for Guatemala; what changes is how soon they arrive. The world simply moves faster around it, so gains come imported and late. Regulation and politics could slow or redirect any path. How Guatemalans and their 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. Guatemala's own signals would arrive earlier than the growth data: the order books of the maquila textile plants, adoption in the Spanish-language call center and outsourcing firms, and any hyperscaler or power export contracts tied to the SIEPAC grid.
If growth goes explosive
Explosive is the wrong word here. At 6.1% growth a year, Guatemala would trail both the frontier and its own region. The United States would be compounding at several times that rate, and the Latin American median would run higher too. This is catch-up that does not catch up: the gap widens even as Guatemala outpaces its own past. Still, 6.1% doubles the economy in under twelve years, so a child born today would finish school in a country twice as rich. Rising labor demand and wages at home would ease the pressure to emigrate, which matters for a country that sends so many workers north. There is a way this leaves Guatemala worse off. Its skilled young people are its main asset, and a fast world bids hard for builders and engineers, so brain drain could deepen rather than ease. Compute rented from abroad can be repriced or cut off by others. The hedge is to keep talent and own capacity, not rent both. Even a modest lift would test the state — the tax authority SAT, the electricity regulator CNEE, municipal permitting offices and the courts — whose weakness already caps what Guatemala can build.
What Guatemala can do now
Three levers follow from the scores, and two of them pay off whether or not AGI arrives. The first is AI diffusion, at 1.8. Digital skills, permissive deployment rules and digitizing government services carry real weight even in the skeptic's world, so this is a no-regret move Guatemala can start today. The second is physical build speed, at 2.1. Statutory permitting deadlines, one-stop approvals and building transmission ahead of demand help under every scenario, and they are the same inputs any later data center build would need — a second no-regret step. The third lever is the bet: compute and energy access, at 1.1, Guatemala's lowest score. It barely moves growth if AI stays ordinary, but under fast takeoff it becomes the single biggest lever. Closing it means packaging power, land and quick permits to draw investment, since a $6,598-per-person economy cannot fund the build alone. Guatemala can adapt a working model from its own archetype: Mexico turned Querétaro into a hyperscaler data center cluster by pairing reliable power with pre-zoned land. Open the atlas's policy editor to see how moving these scores reshapes Guatemala's path under each scenario.
Use the policy editor to test how different factor scores change Guatemala’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 Guatemala: 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.