Russia vs Lithuania: AI Job Risk by the Kaliningrad Flank

Lithuania's unusual position: highest Baltic AI exposure, highest Baltic wages

Of the three Baltic states - Estonia, Latvia, and Lithuania - Lithuania has both the highest OECD median wage ($52,898 in 2024) and the highest average AI exposure score (4.95/10 on ILO ILOSTAT 2025 data). The two facts are connected. Lithuania's higher wages reflect a more developed professional services sector with a proportionally larger business and administration professionals cohort - 155,400 workers (10.7% of total employment) scoring 8.0/10. This occupational concentration drives Lithuania's average AI exposure score above both of its Baltic neighbours.

Russia's weighted average of 4.62/10 (ILO ILOSTAT 2025, Rosstat data) is 0.33 points below Lithuania's. The gap reflects the structural difference between a large industrial economy with tens of millions of low-exposure manufacturing and trades workers, and a smaller services-concentrated economy where professional and administrative work dominates. Both data series are computed by WorldJobsData from ILO ILOSTAT (CC BY 4.0), 2025 data year, using ISCO-08 occupation groups.

Lithuania workforce AI exposure - 2025 data

Lithuania's ILO ILOSTAT 2025 data covers 1,456,000 workers across detailed ISCO-08 sub-major occupation groups. Statistics Lithuania (Statistikos departamentas) is the national data provider. The table below shows Lithuania's top-exposure occupations.

Lithuania's business and administration professionals at 155,400 workers (10.7%) is by far the largest driver of its high average AI score. ICT professionals at 59,700 (4.1%) scoring 8.5/10, science and engineering professionals at 64,700 (4.4%) scoring 7.0/10, and teaching professionals at 66,200 (4.5%) scoring 6.5/10 collectively reinforce the upper distribution. Sales workers account for 72,900 (5.0%) at 5.0/10, health professionals for 59,600 (4.1%) at 5.0/10.

Russia workforce AI exposure - 2025 data

Russia's ILO ILOSTAT 2025 data covers 73,457,000 workers. Rosstat (the Federal State Statistics Service) provides national data to the ILO. The table below shows Russia's ISCO-08 major group data.

Russia's Professionals group at 20.7 million workers (28.2%) scoring 6.5/10 is the dominant category - at major-group ISCO level this includes the equivalent of Lithuania's ICT professionals, business and administration professionals, science and engineering professionals, and teaching professionals combined. Russia's craft and trades (9.2M, 12.5%) and plant operators (8.9M, 12.1%) together represent 21.6% of total employment at 2.5-3.0/10, pulling Russia's overall average substantially below Lithuania's more services-concentrated profile.

Why Lithuania scores 0.33 points above Russia

The gap between Lithuania's 4.95 and Russia's 4.62 is primarily explained by two structural differences. First, Lithuania's business and administration professionals at 10.7% of employment scoring 8.0/10 create a large high-exposure anchor in the middle of the distribution. Russia's equivalent professionals are absorbed into the broader Professionals major group at 6.5/10 rather than at 8.0/10 - the granularity of Lithuania's ISCO reporting captures higher-exposure sub-groups within the professional category that Russia's aggregate reporting does not separately enumerate.

Second, Russia's low-exposure groups are proportionally much larger. Russia's craft and trades workers, plant operators, agricultural workers, and elementary occupations together represent 33.3% of total employment at scores of 2.0-3.0/10. Lithuania's equivalent low-exposure groups represent a smaller share of a more service-oriented workforce. When the bottom of the distribution is smaller as a percentage, the weighted average rises even if the top is similar.

The safest jobs from AI in Lithuania

Lithuania's lowest AI exposure occupations follow the same pattern as its Baltic neighbours - physical, outdoor, and variable-environment work resists current AI capabilities.

Lithuania's cleaners and helpers at 50,900 workers (3.5%) form the largest single low-exposure group, scoring 1.5/10. Drivers and mobile plant operators at 70,000 (4.8%) score 2.5/10 - the largest overall low-exposure category by headcount. Lithuania's emigration to Western Europe since EU accession has particularly affected younger, educated workers in higher-exposure categories. Physical and elementary workers have emigrated in smaller proportions, making these groups slightly more stable within the domestic labour pool.

Economy comparison: Russia vs Lithuania

The table below uses World Bank Open Data (CC BY 4.0) and UNDP Human Development Report 2025 (2023 data year, CC BY 3.0 IGO).

Lithuania's GDP per capita of $32,959 (World Bank, 2025) is 88% higher than Russia's $17,547. Lithuania's OECD median wage of $52,898 (2024) is the highest of the three Baltic states. Both countries have unemployment rates that reflect structural dynamics beyond simple demand: Russia's low 2.13% reflects military mobilisation reducing the civilian labour pool; Lithuania's 6.73% reflects ongoing emigration reshaping the working-age population. Lithuania's HDI of 0.895 (rank 39) places it 25 ranks above Russia (rank 64, HDI 0.832).

The Kaliningrad tension: Lithuania's unique border exposure

Lithuania is the only NATO and EU member state with a land border that touches both Russia (via the Kaliningrad exclave) and Belarus. This geopolitical position became acute in July 2022 when Lithuania implemented EU sanctions by restricting rail transit of certain goods - including steel and iron - between mainland Russia and Kaliningrad. Russia described the restriction as "openly hostile," and the European Commission issued guidance clarifying what transit was permissible. The dispute was resolved without escalation, but it demonstrated Lithuania's position as a direct interface between EU sanctions enforcement and Russian sovereign interests.

For AI deployment context, Lithuania operates as a full EU and NATO member with complete access to Western cloud infrastructure, frontier AI models, and enterprise software. Russian employers face US and EU export controls that restrict access to equivalent technology. The 0.33-point gap in theoretical AI exposure scores understates the actual current difference in AI disruption risk: Lithuanian workers at 4.95/10 average face tools that are commercially available and actively deployed; Russian workers at 4.62/10 average face constraints on acquiring those tools through Western providers.

All three Baltic states have experienced significant emigration since EU accession in 2004. Lithuania's population declined from roughly 3.5 million in 2004 to approximately 2.8 million by 2025 (Statistics Lithuania). A workforce of 1.46 million from a population of 2.8 million reflects a tight labour market with high emigration of working-age people. AI displacement of Lithuania's 155,400 business and administration professionals - a highly mobile group - could accelerate further emigration, particularly to Germany, UK, and Ireland where comparable professional roles remain in demand.

What this means for workers in both countries

For Lithuanian workers, the most immediate AI risk sits in the business and administration professionals category: 155,400 workers at 8.0/10 are performing financial, accounting, human resources, and management consulting tasks that current AI tooling can partially or substantially automate. ICT professionals at 59,700 (4.1%) scoring 8.5/10 face a different dynamic - they are both high-exposure and typically the workers deploying AI tools, making their displacement less straightforward than clerical workers. Science and engineering professionals at 64,700 (4.4%) scoring 7.0/10 face moderate near-term risk in routinisable engineering tasks.

For Russian workers, the 20.7 million Professionals (6.5/10) and 10.9 million Technicians (5.5/10) represent the primary at-risk population - together 43% of the workforce at scores above the Russian weighted average. The practical deployment timeline for AI tools in Russia is constrained by access restrictions to Western AI infrastructure, but Russia's domestic AI programs and partnerships with non-sanctioning technology providers are reducing this gap. The workers in Russia most resembling Lithuania's high-exposure business and administration professionals - financial analysts, accountants, management consultants, HR professionals - are embedded within the ILO's Professionals major group at 6.5/10 and face real but timeline-uncertain disruption.

Across both countries, the physical-work anchor holds: drivers (2.5/10), labourers (2.0/10), cleaners (1.5/10), and agricultural workers (1.5/10) remain resistant to current AI capabilities regardless of which country they work in. The floor of AI exposure is consistent across both sides of the Kaliningrad border.