Singapore
GDP per capita to 2060, by scenario
Constant-rate scenario path; the 2060 endpoint levels are illustrative, not forecasts.
Factor profile
High-income, skilled economies with strong AI adoption, including large aging economies whose diffusion scores offset weaker demographics.
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.
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 Singapore starts
Singapore enters the AGI era as a high-trust diffuser: rich, skilled and quick to absorb new technology. The scores show why. Cyber resilience is 4.9 out of 5, among the world's highest. AI diffusion capacity is 4.6, language inclusion 4.7, and demographics and migration 4.7, far above the archetype's median, because Singapore draws skilled workers the world over. Its institutions, from MAS to EDB and a working Smart Nation program, turn capability into use. The constraints are physical. Compute and energy access scores 3.2 on scarce land and imported power. Climate and water resilience is 2.4. Catch-up headroom is 1.1, because a $98,814-per-person economy has little convergence room left. Ten-year trend growth is 3.2% a year, at high income. Every scenario turns on whether power and chips keep pace.
The three paths
These are simulations, not forecasts. The Modest path is the baseline; the two AGI scenarios fork from it. Under the Modest scenario, AI stays a normal technology. Singapore would gain a small lift: 3.6% growth a year, 49th of 157, the economy doubling in about twenty years. Diffusion and skills would keep it ahead of peers, but growth stays near trend. Under Gradual takeoff, growth would climb for two decades and reach 15.7% a year once AGI matures around 2045, placing Singapore 7th in the world. An economy growing at 15.7% doubles in under five years. The long ramp gives its institutions time to turn a diffusion edge into new industries. Under Fast takeoff, growth would reach 27.4% a year from the early 2030s, a doubling roughly every three years. Yet Singapore's rank would slip to 10th, because a fast world rewards the frontier compute and chip capacity it does not own. Regulation and politics could slow or redirect any of these paths. How Singaporeans 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. Watch leading indicators, not GDP, and watch them live. 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. Singapore's own signals would arrive sooner than the growth data: new hyperscaler commitments under the Green Data Centre Roadmap, fresh power and cooling allocations from the energy authority, submarine cable landings, and the pace of AI adoption across MAS-regulated finance.
If growth goes explosive
Explosive is relative. At 15.7% growth a year, Singapore would still trail the frontier, because the United States would compound faster still. But it would run well ahead of its region and its own history. The economy would double in under five years, so a child starting school would finish it in a country several times richer. Composition would shift toward hosted computing, AI-enabled finance and services. Singapore is an aging country that imports labor; it has no emigrant workforce to draw home. Faster growth would raise wages and labor demand, deepening its pull on skilled migrants. There is a way this leaves Singapore worse off. Its edge is diffusion, not frontier capability, and it rents compute and access rather than owning them. If the US-China rivalry turns exclusionary, the neutral-ground bet could break, and the models and chips Singapore relies on could be repriced or withheld. The hedge is to secure alliance access and build owned capacity. Even then, the pace-setter would move from the trading floor to the state, testing how fast the energy authority, PUB and planners can supply power, water and land.
What Singapore can do now
Three levers follow from the scores, and two pay off whether or not AGI arrives. Start with climate and water resilience, low at 2.4. Flood, heat and water defenses protect a low-lying island under every scenario, and water-efficient cooling is the very input a data center build would need. That is a no-regret move. The second protects a strength rather than closing a gap: keep the open trade, investment and skilled migration, and the institutions, that give Singapore its diffusion edge. These carry weight even in the skeptic's world, so guarding them is also no-regret. The third lever is the bet. Compute and energy access, at 3.2, carries the most weight of all and climbs steeply toward a fast takeoff. It barely moves growth if AI stays ordinary. Closing it means securing chips through alliances and packaging power, land and fast permits for hyperscale investment. Singapore could adapt the United Kingdom's push to build sovereign public compute, such as its AI Research Resource, to cut dependence on rented capacity. A cautious government can act on the two no-regret levers today and lose nothing. To see how moving these scores reshapes Singapore's path under each scenario, open the atlas's policy editor.
Use the policy editor to test how different factor scores change Singapore’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 Singapore: 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.