Lithuania
GDP per capita to 2060, by scenario
Constant-rate scenario path; the 2060 endpoint levels are illustrative, not forecasts.
Factor profile
Firms moved factory and office work here for its labor cost: assembly lines, garments, call centers and IT services sold abroad. AI and robots can increasingly do that work.
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 Lithuania starts
Lithuania enters the AGI era as a stalled middle: middling income, middling scores, and slow growth that leaves it drifting behind faster groups. At about $33,000 per person, it is neither frontier nor fragile. Two scores stand out at the top. Cyber resilience is 4.7 out of 5 and climate resilience 4.9, among the best defended in the world. Its fintech cluster in Vilnius and its world-class scientific-laser industry show real absorptive strength; AI diffusion capacity scores 3.6. But two scores pull hard the other way. Compute and energy access is 1.1, the constraint that most defines it. Demographics and migration is 1.3, reflecting an aging, shrinking population. Ten-year trend growth is 3.2% a year. Every scenario turns on energy and people.
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. Lithuania would grow 3.4% a year, a shade above trend, ranking 62nd of 157. Its fintech and manufacturing strengths would carry it, but the demographic drag would hold it back. Under the Gradual takeoff, growth would climb over two decades and reach 9.3% a year only around 2045, ranking 63rd. An economy growing at 9.3% doubles in under eight years. The long runway lets Lithuania turn skills and institutions into hosted AI services, if the power arrives. Under the Fast takeoff, growth would reach 13.5% a year from the early 2030s, a doubling every five and a half years, and its rank would rise to 53rd, up ten places. A fast world rewards the cyber and climate defenses it already holds. Regulation and politics could slow or redirect any path. How Lithuanians 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 nearly identical until about 2030. 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. Lithuania's own signals would arrive sooner than the growth data: hyperscaler hosting commitments on Lithuanian soil, new generation and grid capacity reaching financial close, the pace of fintech licensing from the Bank of Lithuania, and the order books of its laser and life-science exporters.
If growth goes explosive
Explosive is relative. At 9.3% growth a year under Gradual, Lithuania would run far ahead of its own history, yet trail its region: the European median reaches 10.4% and the frontier would compound at 19.5%. Under Fast, 13.5% would still sit below the regional median of 16.4% and far below the frontier's 39.2%. This is catch-up by Lithuania's own standards, not a break into the lead. At 13.5% the economy doubles about every five and a half years. A child starting school now would finish it in a country several times richer. Faster growth would raise labor demand and wages, which could ease the emigration that has thinned Lithuania's workforce. There is a way this leaves Lithuania worse off. It would host and rent frontier compute rather than own it, inside a chip regime whose rules are set elsewhere. Access could be repriced or cut off by decisions made abroad. The hedge is to build sovereign generation and lock in durable compute access. Even then, the pace-setter would shift to the state, testing how fast the energy regulator, planning offices and courts can permit and count.
What Lithuania 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, low at 2.0. Stronger institutions, more openness to trade and foreign investment, and deeper finance and skills raise growth in the skeptic's world too. The second no-regret lever is demographics, at 1.3. Raising participation among women and older workers, attracting skilled migrants, and investing in schooling so people complement AI rather than compete with it pay off under every scenario. A cautious government can act on both today and lose nothing if the skeptics are right. The third lever is the bet: compute and energy access, at 1.1 and the heaviest-weighted factor. It barely moves growth if AI stays ordinary, but under a fast takeoff it becomes Lithuania's biggest lever. Having just synchronized its grid with continental Europe, Lithuania can add generation, storage and fast permits, then package power and land to draw hyperscale investment. Thailand did this by securing multi-billion-dollar data center commitments from Amazon and Google. Open the atlas's policy editor to see how moving these scores changes Lithuania's path under each scenario.
Use the policy editor to test how different factor scores change Lithuania’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 Lithuania: 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.