Key findings
- General and keyboard clerks score 9.0/10 AI exposure, covering 30,700 workers. Office secretaries, data-entry workers, and administrative support staff face the highest direct LLM substitution risk in the Finnish economy. Finnish banking (OP Financial Group, Nordea's Finnish operations) and public sector administration employ significant numbers in these roles.
- ICT professionals score 8.5/10 AI exposure across 111,700 workers. Finland's tech heritage - Nokia's engineering talent dispersed into hundreds of startups, Rovio's mobile game developers, and Helsinki's growing startup scene around Slush - created a large ICT workforce now directly in AI's path. Coding, testing, design, and junior developer roles are the most immediately affected.
- Customer services clerks and numerical recording clerks both score 8.5/10, covering 38,800 and 35,400 workers respectively. AI chatbots deployed by Finnish telecoms (Elisa, Telia Finland) and banking services are already reducing call volumes handled by human agents.
- Business and administration professionals score 8.0/10 across 142,400 workers - Finland's largest high-risk group. Accounting, audit, financial analysis, and HR workflows are all heavily AI-augmented. Finland's large public sector (government employs approximately 25% of the workforce) means a significant portion of these professionals work in government agencies where AI adoption is slower but inevitable.
- Personal care workers score 2.0/10 across 195,500 workers - Finland's most sheltered large group. Finland's rapidly aging population (over-65s are approximately 23% of the population and rising) creates structural demand for personal care that AI cannot substitute. This is Finland's most important employment buffer.
2.6 million workers, Eurostat and Statistics Finland (Tilastokeskus) 2025 data
Employment data comes from Eurostat lfsa_egai2d and Statistics Finland (Tilastokeskus) Labour Force Survey, using ISCO-08 major group classifications. Data year: 2025, covering approximately 2.57 million workers. Finland's formal employment rate is very high by European standards - informal employment is estimated at just 2%, meaning the 2.6M figure captures close to the full working population. This makes Finland's AI exposure data more complete than for countries with large informal sectors.
Finland's OECD average annual wage is $59,597 USD PPP (2024), placing it in the middle tier of OECD countries and below the Nordic neighbours Norway ($74,864) and Denmark. The relatively high wage level means the economic case for AI automation of clerical and professional roles is strong - the cost of an AI tool is far below the cost of a Finnish office worker in absolute terms.
The most AI-exposed occupations in Finland
General and keyboard clerks score 9.0/10 - the highest of any occupation group in Finland - covering 30,700 workers. These workers handle data entry, administrative document processing, scheduling, office correspondence, and accounting support tasks. In Finland's banking sector, public administration, and corporate services, these roles are directly in the path of large language model automation. AI tools can now handle the core tasks of these roles with minimal human oversight.
ICT professionals score 8.5/10 AI exposure across 111,700 workers. Finland's tech heritage runs deep: Nokia's collapse in the early 2010s dispersed thousands of engineers into the startup ecosystem and created the talent base for companies like Rovio (Angry Birds), Supercell (Clash of Clans), and hundreds of B2B software companies. The annual Slush conference in Helsinki marks Finland's position as a serious European tech hub. AI coding tools - GitHub Copilot, Cursor, and similar products - directly reduce the coding hours per feature required from junior developers, and this is already affecting hiring decisions in Helsinki's tech sector in 2025.
Customer services clerks score 8.5/10 across 38,800 workers. Finnish telecoms and banking services have deployed AI chatbots extensively. Numerical and material recording clerks score 8.5/10 across 35,400 workers. Business and administration professionals score 8.0/10 across 142,400 workers - Finland's largest single high-risk group, working across corporate accounting, financial analysis, HR, and consulting. Business and admin associate professionals score 7.5/10 across 154,300 workers.
| Occupation group | Workers | AI score | Robotics risk |
|---|---|---|---|
| General and keyboard clerks | 30.7K | 9.0/10 | 2.0/10 |
| ICT professionals | 111.7K | 8.5/10 | 1.0/10 |
| Customer services clerks | 38.8K | 8.5/10 | 4.0/10 |
| Numerical and recording clerks | 35.4K | 8.5/10 | 4.5/10 |
| Business and admin professionals | 142.4K | 8.0/10 | 1.5/10 |
| Business and admin associate professionals | 154.3K | 7.5/10 | 1.5/10 |
| ICT technicians | 28.2K | 7.5/10 | 2.5/10 |
| Science and engineering professionals | 163.2K | 7.0/10 | 2.0/10 |
Finland's knowledge economy and the AI paradox
Finland is consistently rated as one of the most advanced knowledge economies in the world. PISA scores, digital infrastructure (Finland was among the first countries to declare broadband internet a legal right), and a tradition of investing heavily in education have built a workforce with high concentrations in precisely the occupations AI targets most directly. This is not a coincidence - it is the defining feature of AI's disruption pattern.
The country that invested most in training knowledge workers faces the sharpest near-term AI exposure in the knowledge sector. Finland's public sector employs approximately 25% of the workforce in roles across healthcare, education, government administration, and public safety. This large public sector provides a degree of structural protection against rapid displacement - government bodies move more slowly on AI adoption than private sector firms. But this is a delay, not a prevention.
Compare with Sweden, which has a very similar knowledge economy profile and weighted average AI exposure of around 5.0/10. Or Norway, where the oil sector adds a buffer through high-wage physical labour. Or Denmark, where a similar professional services concentration drives comparable exposure. The Nordic knowledge economies cluster in the 4.9-5.3/10 range - advanced enough to build vulnerable knowledge workforces, stable enough that disruption timelines are measured in years rather than months.
"Finland's 4.91/10 weighted AI exposure reflects the paradox of the knowledge economy: the education investments that built Finland's prosperity concentrated workers in precisely the occupations AI targets first."
The safest jobs from AI in Finland
Food preparation assistants score 1.5/10 AI exposure, covering 29,900 workers. Kitchen and food preparation work is entirely physical, requires constant sensory adaptation, and has no practical AI substitution path. Refuse workers and other elementary workers score 1.5/10 across 11,300 workers - outdoor, physical, location-specific work that AI cannot touch. Street and related sales workers score 1.5/10 across 3,500 workers.
Personal care workers score 2.0/10 across 195,500 workers - Finland's largest sheltered group and its most important employment buffer. Finland's aging population drives structural demand for personal care that will increase regardless of AI development. Building and related trades workers score 2.0/10 across 93,200 workers. Drivers and mobile plant operators score 2.5/10 across 118,500 workers - the AI exposure is low, but drivers face 7.5/10 robotics risk on a longer autonomous vehicle timeline. Personal service workers score 2.5/10 across 122,100 workers.
| Occupation group | Workers | AI score | Robotics risk |
|---|---|---|---|
| Food preparation assistants | 29.9K | 1.5/10 | 6.5/10 |
| Personal care workers | 195.5K | 2.0/10 | 2.5/10 |
| Building and related trades workers | 93.2K | 2.0/10 | 4.0/10 |
| Personal service workers | 122.1K | 2.5/10 | 5.0/10 |
| Drivers and mobile plant operators | 118.5K | 2.5/10 | 7.5/10 |
| Metal and machinery trades | 85.4K | 3.0/10 | 6.5/10 |
What this means for Finnish workers right now
Finland's welfare state and active labour market policies provide stronger transition support than most countries face. The TE Services (Tyollisyys- ja elinkeinopalvelut - Employment and Economic Development services) system offers retraining programs, and Finland has experimented with approaches like the universal basic income pilot (2017-2018). This institutional infrastructure means displaced workers have more support than their counterparts in, say, the US or UK - but it does not prevent the displacement itself.
For the 111,700 ICT professionals and 142,400 business and admin professionals, the near-term risk pattern mirrors what we see across Northern Europe: wage compression before outright job loss, then slower replacement hiring when positions fall vacant. Finnish employers will reduce headcount through attrition - not replacing leavers - rather than mass redundancies, which are more legally and socially costly in Finland than in Anglo-Saxon markets.
The personal care sector (195,500 workers at 2.0/10 AI exposure) is the clearest long-term growth area. Finland's government has set legally binding staffing minimums for elderly care, which create a structural floor for care employment regardless of AI development. Workers transitioning from administrative roles to care work face a significant wage adjustment, but care work in Finland pays more than in many comparable economies due to unionisation and public sector involvement.
For broader context on how Finland compares globally, see our US vs World AI job risk analysis, or compare with Sweden and Norway for a Nordic comparison.
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Methodology
Employment figures are from Eurostat lfsa_egai2d and Statistics Finland (Tilastokeskus), using ISCO-08 occupation group classifications. Data year: 2025, covering approximately 2.57 million workers. AI exposure scores reflect the proportion of an occupation's core tasks that current AI systems can perform or significantly augment - not predictions of job loss rates. Informal employment is approximately 2% in Finland. Scores are research-based estimates informed by Frey-Osborne (Oxford 2017), OECD task-automation analysis, and IMF Gen-AI impact studies (2024).
Frequently asked questions
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Related analyses
Data sources
- Eurostat - Labour Force Survey (lfsa_egai2d), Finland, 2025
- Statistics Finland (Tilastokeskus) - Labour Force Survey 2025
- OECD - Average Annual Wages 2024 (USD PPP, $59,597 Finland)
- Frey, C.B. and Osborne, M.A. (2017). The future of employment. Technological Forecasting and Social Change.
- IMF - Gen-AI: Artificial Intelligence and the Future of Work (2024)