Gambia
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
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 Gambia starts
Gambia enters the AGI era as a reform climber, one of sixteen countries growing steadily from a low base while their institutions improve. The distinguishing score is catch-up headroom at 4.7 out of 5, near the top of the map. This measures how far a country can grow simply by adopting what richer economies already use. Since the 2017 democratic transition, Gambia has rebuilt public finances and reopened to investment, and its demographics score 3.1 reflects a young, growing workforce. The constraints are physical. Compute and energy access sits at the floor, 1 out of 5, and AI diffusion capacity at 1.3. Grid power reaches only part of the population. At $919 GDP per person, Gambia is lower-income, and at $3bn it is one of the smaller economies here. Ten-year trend growth is 4.7% 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. Gambia would hold close to trend, 4.7% growth a year, ranking 31st of 157. It ranks high here because catch-up headroom counts for most when AI stays ordinary. That pace doubles the economy in about fifteen years. Under Gradual takeoff, growth would climb over two decades and reach 5.7% a year once AGI matures around 2045, ranking 119th. The long runway lets reform momentum and steady adoption compound, doubling the economy in roughly twelve and a half years. Under Fast takeoff, growth would arrive from the early 2030s but reach only 4.0% a year, ranking 139th, a slide of twenty places. In this world Gambia would grow more slowly than it would have without AGI at all. A fast takeoff rewards the compute and geopolitical weight Gambia lacks, and it reprices the labor-intensive work Gambia depends on. Politics could slow or redirect any of these paths. How Gambians and their government respond to transformative AI is a variable the model holds constant.
How you would know which world you are in
The three scenarios look almost the same 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. 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 a gradual one; a fade back to trend a modest one. Gambia's own signals would arrive earlier: household electricity connection rates, progress on the OMVG regional interconnector, submarine cable capacity, mobile money uptake, and hotel booking books.
If growth goes explosive
Explosive is relative, and for Gambia the rates are modest by any measure. Even at its best, 5.7% growth a year, Gambia would sit near its region's median and far behind the frontier, which would compound at 19.5%. Under Fast takeoff the gap widens: the frontier near 39.2% while Gambia slips below its own trend. So this is not an explosive story for Gambia; it is a relative-decline risk. At 5.7% growth, a child born today would reach her teens in an economy twice as large, built on tourism, groundnuts and re-export trade. Faster growth at home would raise labor demand and wages, easing the pressure to emigrate for work. The honest downside is the kicked-away ladder. The rungs Gambia is climbing, from labor-intensive services to farm and assembly work, are the first that automation reprices. The hedge is to diversify early and move toward work that machines complement rather than replace. Even so, the pace-setter would shift to the state, testing whether NAWEC can deliver power and whether ministries and Banjul's port and customs can permit and count fast enough.
What Gambia can do now
Three levers follow from the scores, and two pay off whether or not AGI arrives. The first is AI diffusion, low at 1.3. Digital skills, permissive deployment rules and digitizing government services first carry real weight even in the skeptic's world, so this is a no-regret move. The second is physical build speed, at 2.1. Permitting reform with statutory shot clocks, pre-zoned land and transmission built ahead of demand helps the economy under every scenario, another no-regret step. The third lever is the bet. Compute and energy access, at 1 and the highest-weighted factor, barely moves growth if AI stays ordinary, but under a fast takeoff it becomes Gambia's single biggest lever. A $3bn economy cannot fund it alone, so it needs regional grid links and co-investment. Gambia can adapt a neighbor's model: Senegal built a national data center at Diamniadio to host state data at home. 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 Gambia's path under each scenario.
Use the policy editor to test how different factor scores change Gambia’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 Gambia: 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.