All Occupations Ranked by AI Exposure
39 ISCO-08 occupation groups · data year 2025 · Tier A Full data - employment, wages, AI scores, growth projections
| ISCO | Occupation Group | AI Exposure | Robotics Risk | WFH Potential | Employment | Median Wage |
|---|---|---|---|---|---|---|
| 41 | General and keyboard clerks | 9.0/10 | 2.0/10 | 9.0/10 | 10K | $20,293 |
| 25 | Information and communications technology professionals | 8.5/10 | 1.0/10 | 9.5/10 | 60K | $31,938 |
| 42 | Customer services clerks | 8.5/10 | 4.0/10 | 8.0/10 | 15K | $20,293 |
| 43 | Numerical and material recording clerks | 8.5/10 | 4.5/10 | 7.5/10 | 30K | $20,293 |
| 24 | Business and administration professionals | 8.0/10 | 1.5/10 | 9.0/10 | 155K | $31,938 |
| 33 | Business and administration associate professionals | 7.5/10 | 1.5/10 | 8.5/10 | 63K | $23,393 |
| 35 | Information and communications technicians | 7.5/10 | 2.5/10 | 8.5/10 | 6K | $23,393 |
| 21 | Science and engineering professionals | 7.0/10 | 2.0/10 | 8.0/10 | 65K | $31,938 |
| 26 | Legal, social and cultural professionals | 7.0/10 | 1.0/10 | 7.5/10 | 49K | $31,938 |
| 12 | Administrative and commercial managers | 6.5/10 | 1.5/10 | 8.0/10 | 57K | $37,005 |
| 23 | Teaching professionals | 6.5/10 | 1.5/10 | 6.0/10 | 66K | $31,938 |
| 44 | Other clerical support workers | 6.0/10 | 4.5/10 | 4.0/10 | 10K | $20,293 |
| 31 | Science and engineering associate professionals | 5.5/10 | 4.0/10 | 4.0/10 | 31K | $23,393 |
| 11 | Chief executives, senior officials and legislators | 5.0/10 | 1.0/10 | 6.5/10 | 44K | $37,005 |
| 13 | Production and specialised services managers | 5.0/10 | 3.5/10 | 5.0/10 | 33K | $37,005 |
| 22 | Health professionals | 5.0/10 | 2.5/10 | 2.0/10 | 60K | $31,938 |
| 32 | Health associate professionals | 5.0/10 | 4.0/10 | 2.0/10 | 13K | $23,393 |
| 34 | Legal, social, cultural and related associate professionals | 5.0/10 | 2.0/10 | 4.0/10 | 23K | $23,393 |
| 52 | Sales workers | 5.0/10 | 6.0/10 | 2.5/10 | 73K | $15,448 |
| 14 | Hospitality, retail and other services managers | 4.5/10 | 3.0/10 | 3.0/10 | 10K | $37,005 |
| 73 | Handicraft and printing workers | 4.0/10 | 5.0/10 | 2.0/10 | 7K | $19,114 |
| 01 | Commissioned armed forces officers | 3.5/10 | 2.0/10 | 2.0/10 | 4K | N/A |
| 61 | Market-oriented skilled agricultural workers | 3.5/10 | 7.0/10 | 1.0/10 | 26K | N/A |
| 74 | Electrical and electronic trades workers | 3.5/10 | 3.5/10 | 1.5/10 | 14K | $19,114 |
| 81 | Stationary plant and machine operators | 3.5/10 | 8.0/10 | 1.5/10 | 26K | N/A |
| 72 | Metal, machinery and related trades workers | 3.0/10 | 6.5/10 | 1.0/10 | 57K | $19,114 |
| 51 | Personal service workers | 2.5/10 | 5.0/10 | 1.0/10 | 54K | $15,448 |
| 62 | Market-oriented skilled forestry, fishing and hunting workers | 2.5/10 | 5.5/10 | 0.5/10 | 3K | N/A |
| 75 | Food processing, woodworking, garment and other craft workers | 2.5/10 | 5.5/10 | 1.5/10 | 41K | $19,114 |
| 82 | Assemblers | 2.5/10 | 8.5/10 | 0.5/10 | 11K | N/A |
| 83 | Drivers and mobile plant operators | 2.5/10 | 7.5/10 | 0.5/10 | 70K | N/A |
| 53 | Personal care workers | 2.0/10 | 2.5/10 | 0.5/10 | 30K | $15,448 |
| 54 | Protective services workers | 2.0/10 | 3.5/10 | 0.5/10 | 20K | $15,448 |
| 71 | Building and related trades workers (excl. electricians) | 2.0/10 | 4.0/10 | 0.5/10 | 62K | $19,114 |
| 93 | Labourers in mining, construction, manufacturing and transport | 2.0/10 | 6.5/10 | 0.0/10 | 54K | $13,244 |
| 91 | Cleaners and helpers | 1.5/10 | 6.0/10 | 0.0/10 | 51K | $13,244 |
| 92 | Agricultural, forestry and fishery labourers | 1.5/10 | 6.0/10 | 0.0/10 | 20K | $13,244 |
| 94 | Food preparation assistants | 1.5/10 | 6.5/10 | 0.0/10 | 7K | $13,244 |
| 96 | Refuse workers and other elementary workers | 1.5/10 | 6.0/10 | 0.0/10 | 27K | $13,244 |
AI/robotics/WFH scores are research-based estimates (Frey-Osborne, OECD, IMF 2024), not official statistics. Hover occupation name for rationale. Employment from: Eurostat lfsa_egai2d (Eurostat open dissemination policy), Eurostat SES 2022 (mean annual gross earnings, EUR).
AI Disruption Context
World Bank indicators showing when disruption will arrive and how resilient the workforce is.
Risk Velocity
7.5/10
Disruption arriving (3-7 years)
Recovery Resilience
7.2/10
High resilience - workers can pivot
Demographic Alignment
Labor shortage solver
Aging workforce means automation fills critical gaps
Source: World Bank Open Data (CC BY 4.0) - IT.NET.BBND.P2, IT.NET.SECR.P6, HD_HCIP_OTJL_TO, SP social protection indicators.
Frequently Asked Questions
Which job is most at risk from AI in Lithuania?
General and keyboard clerks has the highest AI exposure score in Lithuania at 9.0/10. This occupation involves routine information handling that current AI systems can perform effectively.
What is the average AI exposure score in Lithuania?
The workforce-weighted average AI exposure score in Lithuania is 5.0/10, covering 1.5M workers across 39 occupation groups. Each group is weighted by its share of total employment.
Which jobs are safest from AI in Lithuania?
Cleaners and helpers has the lowest AI exposure score in Lithuania at 1.5/10. These roles require physical presence or manual dexterity in unpredictable environments that current AI cannot automate at scale.
When will AI disruption arrive in Lithuania?
Based on digital infrastructure readiness, Lithuania scores 7.5/10 for AI Risk Velocity. Disruption arriving (3-7 years). This is derived from World Bank broadband and secure internet server data.
How well can Lithuania's workforce adapt to AI disruption?
Lithuania scores 7.2/10 for Workforce Recovery Capacity. High resilience - workers can pivot. This combines the World Bank Human Capital Index on-the-job learning score and social protection coverage data.
Which occupation pays the most in Lithuania?
The highest-paid occupation in Lithuania is Chief executives, senior officials and legislators at $37,005 per year. The lowest-paid is Cleaners and helpers at $13,244 per year.
Is automation good or bad for Lithuania's workforce?
Lithuania is classified as 'Labor shortage solver'. Aging workforce means automation fills critical gaps. This is based on World Bank old-age dependency ratio and fertility rate data.
Where does the Lithuania workforce data come from?
The Lithuania data comes from: Eurostat lfsa_egai2d (Eurostat open dissemination policy); Eurostat SES 2022 (mean annual gross earnings, EUR); OECD Average Annual Wages (USD PPP, 2024). All data is from official government or intergovernmental sources and is freely available at worldjobsdata.com.
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