← Research themes · Last updated 3 Nov 2026

Floating islands above a sea of clouds, some with glowing domes, linked by faint paths of light

Best countries to live in a post-AGI world

A transparent, adjustable ranking. Change the weights and see how the list moves.

Working thesisIn a post-AGI world the safest countries are either (A) frontier or sovereign-AI countries that control the technology, or (B) countries with few AI-relevant resources (minerals, cheap power, water, land), which makes them less likely to be fought over.

The table combines public indicators into scores that are computed in your browser. The scores are computed by this site from the sourced inputs; they are a way to explore the thesis, not a prediction.

Ranking: Route A, Route B and combined

Scores are computed in your browser from sourced indicators: see every raw indicator row

Adjust weights
All scores 0–100, computed by this site from the sourced indicators shown. Indicator years: HDI 2023, rule of law 2025, electricity 2025, minerals 2025, armed conflict 2021–2025. Source: Epoch AI (Notable AI Models, Frontier AI Models, GPU Clusters); UNDP HDI, V-Dem, Ember/Energy Institute, FAO/World Bank, USGS via Our World in Data; UCDP/PRIO [2] [3] [4] [5] [6] [7] [8] [9] [10] · built 24 Oct 2026

Before you act on this ranking, check fiscal fragility. The ranking scores safety after AGI. Fragility on the way to AGI scores who has the debt, deficits, interest bills and unrest that could break them during the transition. The US tops both lists, and 7 of the default top 15 fail a simple fiscal check.

What to watch

  • Epoch AI frontier-model and GPU-cluster counts by country (they change Route A fastest).
  • National sovereign-AI compute programmes (EU, Gulf, India, Japan, UK).
  • Critical-mineral export controls (China's gallium, germanium and graphite rules).
  • Data-centre power and water conflicts, which affect Route B countries that become hosting sites.

Reading

Fragility on the way to AGI: who cracks first

The ranking above asks who is safe after AGI arrives. It doesn't ask who breaks on the way there, and I think that's the bigger near-term risk.

The mechanism.

  1. AI hits office work first. The IMF estimates that about 60% of jobs in advanced economies and 40% in emerging markets are exposed to AI (IMF, Jan 2024). The ILO's narrower measure puts generative-AI exposure at 34% of jobs in high-income countries and 11% in low-income ones (ILO WP140, May 2025).
  2. Those salaries are the tax base. Across the OECD, personal income tax and social security contributions are 49.2% of all tax revenue (23.7% + 25.5% in 2023; OECD Revenue Statistics 2025). If AI profits show up as corporate income in a few countries, while payroll falls everywhere, revenue drops just as spending on benefits, retraining and pensions rises.
  3. A state that starts with high debt, a big deficit and a large interest bill has no room to absorb that. Bond markets then force a choice between austerity, money printing and higher taxes on whatever is still taxable. Each of these feeds populism and unrest, and countries that are already less peaceful have less margin.
  4. The opposite case: low debt, net financial assets (sovereign wealth funds), budget surpluses, and resource or compute rents let a government pay for the transition without asking bond markets first.

None of this says when. It says who has the least room if the transition is fast.

Fiscal fragility on the way to AGI (35 countries, most vulnerable first)

35 rows
#CountryFragility scoreBandGross debt % GDPNet debt % GDPNet interest % revenueDeficit % GDPOld-age dependencyOffice-job share %Peace Index scoreRank on default Combined (of 183)
1United States85.1Fragile126.898.412.28.528.560.72.5351
2France77.2Fragile118.5111.34.75.436.858.32.08375
3Italy72.4Fragile137.9128.58.22.939.749.21.71287
4China70.7Fragile104.4n/a4.58.021.4n/a2.23155
5Brazil70.7Fragile97.068.019.28.116.634.32.333156
6United Kingdom68.8Fragile102.093.46.63.831.164.31.73045
7Belgium67.9Fragile109.895.54.15.333.162.71.60827
8Israel67.5Fragile68.866.77.25.821.157.63.12459
9India66.6Middle83.1n/a25.47.510.813.62.409178
10Greece62.0Middle136.0n/a6.3-0.338.943.81.82878
11South Africa61.2Middle78.076.018.94.410.232.12.308145
12Mexico59.4Middle62.153.623.74.212.627.32.650173
13Poland57.1Middle66.653.06.07.232.052.61.61576
14Spain56.3Middle97.682.14.92.432.946.61.65485
15Japan†56.1Middle199.4127.00.81.451.0n/a1.48990
16Germany52.9Middle64.649.62.04.338.060.31.65747
17Portugal49.2Middle85.180.84.1-0.040.050.51.427106
18Austria49.0Middle82.465.32.94.232.655.91.42160
19Finland48.8Middle90.644.41.34.239.452.91.47884
20Indonesia44.8Middle41.739.516.22.911.115.71.918182
21Türkiye43.3Middle22.518.39.23.115.533.12.605180
22Australia41.9Middle52.634.02.83.228.258.61.602126
23Netherlands41.2Middle45.437.41.62.732.564.31.56625
24Argentina40.9Middle69.3n/a4.0-0.419.038.01.922169
25Saudi Arabia40.7Middle35.427.92.56.54.2n/a2.067114
26Canada†38.1Middle115.69.3-0.22.531.3n/a1.52549
27Sweden36.7Middle35.113.80.22.533.563.31.73289
28New Zealand33.8Resilient57.128.32.64.127.3n/a1.34382
29South Korea32.9Resilient47.37.00.81.329.354.81.83963
30Singapore*30.6Resilient166.4n/an/a-3.719.270.31.43514
31UAE26.9Resilient32.8n/a3.2-1.52.241.71.92750
32Switzerland26.4Resilient38.317.2-0.10.231.664.31.36342
33Norway22.5Resilient40.0-152.5-8.0-13.529.457.71.688123
34Ireland21.5Resilient33.522.51.0-1.424.758.81.37144
35Denmark20.0Resilient26.4-6.9-1.1-1.233.456.11.50420
Click a header to sort. * Singapore's gross debt is shown but not scored, because the government by law invests, rather than spends, what it borrows, and it has no net debt; it is scored on the four inputs it has, so treat it as low-confidence. † Net interest is net of large interest receipts (Japan, Canada), so gross interest is higher. n/a = no data in the source; the score re-weights over the inputs a country has. Data as of 3 Nov 2026.Source: IMF Fiscal Monitor, Oct 2026 [2] [3] [4] [5]

Most likely to crack

1. United States (85.1)

Debt 126.8% of GDP, a deficit of 8.5% and net interest at 12.2% of revenue, with 60.7% of jobs in office work and GPI rank 134 of 163. Dollar status buys time, not immunity.

2. France (77.2)

Debt 118.5% with net debt almost as high (111.3%), a 5.4% deficit and an old population (36.8 over-64s per 100 working-age), plus GPI rank 99.

3. Italy (72.4)

The highest debt here after Japan (137.9%), net interest at 8.2% of revenue and one of the oldest populations (39.7).

4. China (70.7)

Debt 104.4% and a deficit of 8.0%, on the IMF's broad measure, with GPI rank 118. Net debt and the office-job split are missing, so the score uses five inputs.

5. Brazil (70.7)

Net interest takes 19.2% of revenue and the deficit is 8.1%, in a country already at GPI rank 124.

6. United Kingdom (68.8)

Debt 102.0%, net interest 6.6% of revenue and the joint-highest office-job share among large economies (64.3%), so AI reaches a big slice of the tax base.

7. Belgium (67.9)

Debt 109.8%, a 5.3% deficit and 62.7% office jobs.

8. Israel (67.5)

The least peaceful country in the set (GPI 159 of 163), a 5.8% deficit and net interest at 7.2% of revenue.

Just outside: India (9th) and Japan (15th)

India has the heaviest interest bill here (25.4% of revenue), but a young population and few office jobs (13.6%) mean AI hits its tax base less. Japan has 199.4% debt but tiny net interest today. A rise in bond yields would move it up fast.

Most resilient

Denmark (20.0)

Debt 26.4%, net financial assets (net debt −6.9%), a budget surplus and GPI rank 11.

Ireland (21.5)

Debt 33.5%, a surplus and GPI rank 5. The catch, which the score misses, is reliance on corporate tax from a few multinationals.

Norway (22.5)

Net assets of 152.5% of GDP (the oil fund) and a 13.5% surplus: the clearest case of resource rents paying for a transition.

Switzerland (26.4)

Debt 38.3%, a near-balanced budget, negative net interest and GPI rank 3.

UAE (26.9)

Debt 32.8%, a surplus and almost no pensioners yet (2.2 per 100). However, it's GPI rank 73 and its data centres were struck in March 2026 (AP), so the fiscal room comes with physical risk.

Singapore (30.6, low-confidence)

No net debt and a 3.7% surplus, but the highest office-job share in the set (70.3%). Its fiscal position is a buffer for an economy that AI could hit hard.

South Korea (32.9)

Net debt only 7.0% and net interest 0.8% of revenue. On the other hand, it's GPI rank 57 and has 54.8% office jobs.

New Zealand (33.8)

GPI rank 2 and net debt of 28.3%. The 4.1% deficit is the thing to watch.

Where this conflicts with the ranking above, honestly.

  • The US is first on the default Combined ranking and first for fiscal fragility. Both are true: it controls the technology (Route A) and it has the least fiscal room of any large economy here. My reading is that the US is the best place to own AI winners from, but the worst-placed large state to pay for the transition. Expect bond stress, higher taxes or inflation, and political turbulence there before anywhere else at the top of the AI race.
  • Seven of the Combined top 15 fail a simple fiscal check (table below): the US, St Kitts and Nevis, Barbados, St Vincent, the Maldives, Grenada and Cape Verde. Route B ("nothing worth taking") doesn't protect a country from a debt crisis or the loss of its tourism and service income.
  • The UK scores well on Route A (53.1) but is sixth for fragility. France and Belgium also pass liveability easily but sit in the fragile eight.
  • The averaged-routes leaders mostly hold up. Singapore, South Korea and Switzerland are in the resilient group and Germany is mid-table (16th). The US and UK are the exceptions.

My picks after both tests. Places that do well on the post-AGI ranking and have fiscal room: Switzerland, Singapore, Denmark, Norway, Ireland and the Netherlands (23rd of 35 for fragility), plus Luxembourg, Malta and Cyprus from the small-state check (debt of 28–51% of GDP and deficits under 3%). I've moved the US from a "safe" pick to "own its assets, don't rely on its state", and I treat the high-debt islands as no longer safe havens. The interactive ranking itself is unchanged, because its weights are yours to adjust. This section is the cross-check.

The default Combined top 15, checked for fiscal room

Combined rankCountryGross debt % GDP (2026)Overall balance % GDP (2026)My flag
1United States126.8-8.5Fiscal stress
2Saint Kitts and Nevis65.1-9.0Fiscal stress
3Antigua and Barbuda66.8-1.0OK
4Seychelles52.7-1.9OK
5Malta46.4-2.7OK
6Barbados93.8-0.7Fiscal stress
7Saint Vincent and the Grenadines111.6-9.2Fiscal stress
8Maldives130.7-11.9Fiscal stress
9Nauru2.614.5OK
10Luxembourg28.5-2.0OK
11Grenada66.8-11.1Fiscal stress
12Cyprus51.42.3OK
13Saint Lucia78.1-3.1OK
14Singapore166.43.7OK (asset-backed debt)
15Cape Verde109.9-2.0Fiscal stress
"Fiscal stress" means gross debt of at least 90% of GDP or a deficit of at least 6% of GDP in the IMF's 2026 projection.Source: IMF Fiscal Monitor, Oct 2026

How the fragility score works. For each of 35 large or commonly considered countries I take seven inputs and convert each to a percentile rank within the set (0 = least fragile, 100 = most fragile, ties averaged). Percentiles rather than raw values stop one outlier, such as Norway's net assets of 152% of GDP, from flattening everyone else. The score is the weighted mean:

Input Weight Why Source (as of)
Gross government debt, % GDP 20% The stock that has to be rolled over IMF Fiscal Monitor, 2026 projection (Oct 2026)
Net debt, % GDP 10% Credits sovereign wealth funds and other financial assets Same
Net interest, % of revenue 20% How much of each tax dollar already goes to creditors. Computed as (primary balance − overall balance) ÷ revenue Same
Overall deficit, % GDP 15% Whether debt is still rising before any AI shock Same
Old-age dependency 10% Pension and health costs that can't be cut quickly World Bank, 2025 (updated Oct 2026)
Office-job share 10% Share of employment in ISCO groups 1–4 (managers, professionals, technicians, clerks): a proxy for how much of the labour tax base AI can reach. An independent analysis finds this share explains 96% of cross-country variation in an ILO-weighted exposure index (Johnson Zheng, Jun 2026) ILOSTAT, latest year (2024 or 2025)
Global Peace Index score 15% Existing unrest, crime, political instability and conflict IEP GPI 2026 (June 2026)

Rules and limits.

  • Where an input is missing, it's shown as n/a and the score re-weights over the inputs the country has. China lacks net debt and the office-job share; Greece, India, Argentina and the UAE lack net debt; Canada, New Zealand, Saudi Arabia and Japan lack a usable office-job split in ILOSTAT (Japan's release doesn't separate technicians).
  • Singapore reports gross debt of 166% of GDP, but by law the government can't spend what it borrows under the Government Securities Act: the proceeds are invested, and assets exceed liabilities (Singapore MOF). So I show the figure but don't score it. With no IMF net debt or interest data either, Singapore is scored on four inputs and is low-confidence.
  • Net interest flatters countries with large interest receipts, notably Japan (0.8% of revenue on this measure despite debt of 199% of GDP). In Japan's case the risk is rising bond yields feeding through as debt rolls over, which this snapshot can't see.
  • The GPI also penalises militarisation and external wars, not just domestic unrest. That's why Israel and the US score badly on it.
  • Not captured: how concentrated corporate tax is (Ireland's depends on a few multinationals), currency or reserve-currency status (which buys the US time), and political will. The weights are my judgement. I tested three alternatives. With equal weights, the top eight and bottom eight are identical. With fiscal-heavy weights (debt and interest 85%), 7 of each 8 stay. With social-heavy weights (ageing, office jobs and peace 65%), 7 of the top 8 and 6 of the bottom 8 stay. The US comes first in every version.
  • Thirty-five countries is a sample, not the world. Small states that top the Combined ranking are checked separately above.

Signals that the fragility ranking is right

  • Bond yields and term premia rising fastest in the fragile eight, especially the US 10-year, French OAT and UK gilt spreads.
  • Net interest as a share of revenue rising in the next IMF Fiscal Monitor (Apr 2027) for the US, UK, France and Brazil.
  • Payroll and income-tax receipts falling while corporate profits rise, in countries with high office-job shares.
  • GPI or protest counts deteriorating in the fragile group first.

Signals that would prove it wrong (falsifiers)

  • AI productivity gains lift tax revenue faster than costs, so that US and UK deficits narrow below 3% of GDP without austerity by 2028.
  • High-debt countries keep borrowing cheaply through the transition, as Japan has for 30 years, with no bond-market strike anywhere in the fragile eight.
  • Unrest or a fiscal crisis hits a resilient-group country first, which would suggest cohesion and wealth funds aren't the buffer I think they are.
  • Countries with low office-job shares (India, Indonesia, Mexico) are hit as hard as office-heavy ones, which would mean the labour-tax-base channel is wrong.

What to watch

  • IMF Fiscal Monitor (April and October) for debt, deficit and interest updates.
  • Sovereign bond auctions and term premia in the US, UK, France and Japan.
  • Income-tax and payroll receipts versus corporate-tax receipts in office-heavy economies.
  • Global Peace Index 2027 (June) and protest trackers.

Reading

Methodology and limits

Route A (frontier/sovereign AI) is the weighted mean of three indicators, each log-scaled to 0–100 against the leading country:

  • frontier models trained (Epoch AI),
  • notable models since 2023 (Epoch AI),
  • H100-equivalent cluster compute located in the country (Epoch AI GPU clusters).

Route B (little worth taking) is 100 minus the weighted mean of each country's percentile rank on:

  • share of world lithium, cobalt and graphite production (USGS via OWID),
  • electricity generation in TWh,
  • renewable water per person,
  • land area.

Liveability is the weighted mean of:

  • HDI × 100 (UNDP),
  • the rule-of-law index × 100 (V-Dem via OWID),
  • a conflict score: 100 minus 20 for each year with an active UCDP conflict in 2021–2025, with a floor of 0.

Thesis score is either the better of A and B (the thesis says either route works) or their average. Combined = Liveability and the thesis score, weighted as you choose.

Limits

  • Route B is a proxy for "few AI-relevant resources". It also rewards being small and poor, which is why it is combined with liveability.
  • Missing data: countries with gaps are scored on the indicators they have. Hide countries missing more than one indicator (on by default) drops them; untick it to see every country.
  • Epoch counts are by the developer's or operator's headquarters, which flatters the US and China.
  • The indicators cover the present. They say nothing about how AGI actually unfolds, alliances, nuclear protection, climate or immigration rules.
  • The weights are value judgements; the defaults are a starting point, not a finding.

What to watch

  • Add a climate-resilience indicator (e.g. ND-GAIN) once it is fetchable.
  • Add immigration accessibility, which matters if you actually want to move.

Reading

Signals

Signals that would support the thesis

  • Compute is concentrating in a few countries (Epoch GPU-cluster data).
  • Resource competition over critical minerals and power is visible in export controls and data-centre siting.

Signals that would weaken it

  • AI benefits spread quickly through open models and cloud access, so not controlling AI costs little.
  • Small resource-poor countries prove vulnerable anyway, through economic dependence or loss of their service-export base.

What to watch

  • Diffusion of open-weight frontier models.
  • Countries joining or leaving US or Chinese export-control regimes.

Reading

  • Situational Awareness— Leopold Aschenbrenner, 2024-06
    The influential case that AGI becomes a national-security race, which is the Route A logic.
  • International AI Safety Report— International AI Safety Report, 2026
    A consensus review of AI risks, including concentration of power.
  • Trends— Epoch AI, 2026
    Compute and model trends.

Prediction markets

Live prices from public prediction markets, snapshotted by scripts/update_markets.py. A price of 30% means traders pay about 30¢ for a contract that pays $1 if the event happens; treat it as a crowd estimate, not a fact. Polymarket and Kalshi are real-money markets (Kalshi is CFTC-regulated); Manifold uses play money and is often thin. Long-dated and low-volume markets are poorly calibrated. Each market's exact resolution rules on the platform decide what counts, so read them before relying on a headline question.

US vs China

16% bid 16¢ / ask 20¢
134k contracts · 42k open interest · closes 2030-01-01 · as of 2026-10-30 17:06 UTC
6% bid 6¢ / ask 8¢
142k contracts · 45k open interest · closes 2027-01-01 · as of 2026-10-30 17:06 UTC
6% bid 3¢ / ask 12¢
889 contracts · 370 open interest · closes 2027-01-01 · as of 2026-10-30 17:06 UTC
36% bid 25¢ / ask 35¢
228 contracts · 27 open interest · closes 2028-01-01 · as of 2026-10-30 17:06 UTC
58% bid 49¢ / ask 59¢
849 contracts · 120 open interest · closes 2029-01-01 · as of 2026-10-30 17:06 UTC
5%
$67k vol · $33k liquidity · closes 2027-01-01 · as of 2026-10-30 17:06 UTC

Recession risk by country

7%
$2.4M vol · $38k liquidity · closes 2027-01-31 · as of 2026-10-30 17:06 UTC
5%
$16k vol · $3k liquidity · closes 2027-05-01 · as of 2026-10-30 17:06 UTC
9%
$4k vol · $995 liquidity · closes 2027-05-01 · as of 2026-10-30 17:06 UTC
12%
$10k vol · $610 liquidity · closes 2027-02-16 · as of 2026-10-30 17:06 UTC

Taiwan (chip supply) risk

3%
$441k vol · $65k liquidity · closes 2027-01-01 · as of 2026-10-30 17:06 UTC
10%
$3.6M vol · $196k liquidity · closes 2028-01-01 · as of 2026-10-30 17:06 UTC

Safety nets

69%
Ṁ5k play-money · 49 traders · closes 2032-12-31 · as of 2026-10-30 17:06 UTC
61%
Ṁ12k play-money · 50 traders · closes 2039-12-31 · as of 2026-10-30 17:06 UTC

Snapshot fetched 2026-10-30 17:06 UTC from public APIs (Polymarket Gamma/CLOB, Kalshi trade API, Manifold v0). Prices are what traders are paying, not my forecasts and not advice; thin or long-dated markets can be far off. Sparklines show daily prices over up to 120 days. Metaculus: API now requires an authenticated account token (HTTP 403 without one) and the website is behind a bot challenge, so Metaculus forecasts are not included. Add a ref type with a personal token later if wanted.

How to add a market

Add a ref to "markets" → "groups" → "refs" in src/themes/<slug>.json: {"platform":"polymarket","event":"<slug after /event/ in the URL>"}, {"platform":"kalshi","event":"<EVENT_TICKER>"} or {"platform":"manifold","id":"<market id or slug>"}. Optional: "markets" (list of specific sub-market slugs or tickers), "max", "sort" (date, prob or api). Then run python3 scripts/update_markets.py <slug> and rebuild.

Notes & journal

Dated observations from src/notes/post-agi-countries.md. Add a new entry with a ## YYYY-MM-DD Title heading.

24 Oct 2026

First version of the scoring

Default weights: liveability 40, thesis 60. Try "average" instead of "max" for the thesis score to see which countries satisfy both routes.

Data behind this figure