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Top Careers and the Impact of AI: What the Research Says
The short answer: the careers with the strongest outlook pair growing demand with work that AI can help with but not take over. That means healthcare and care work, skilled trades tied to energy and buildings, and the technical roles that build and secure AI and data systems. The careers under the most pressure are routine clerical and administrative jobs, which are both the most exposed to AI and already shrinking. Employers surveyed by the World Economic Forum expect 170 million jobs to be created and 92 million displaced between 2025 and 2030, a net gain of 78 million. The International Labour Organization finds that about one in four workers worldwide is in a job with some exposure to generative AI, but only 3.3% are in the most exposed group.
This guide covers the global picture. For tables of the top careers where you live, read the region guides: the US, the UK and Europe, India and Asia-Pacific (including Australia), Africa, and South America.
Exposure to AI is not the same as losing your job
Almost every study of AI and work measures exposure: how much of a job’s tasks an AI system could do or speed up. A highly exposed job can go two ways. AI can take over the tasks (automation), or it can make the person doing them faster and more valuable (augmentation). The ILO concludes that for most occupations the likely result is transformation rather than replacement, because most jobs still contain tasks that need a person. BLS says the same about its own ratings: exposure “does not imply job loss, productivity gains, automation probability, or wage effects.”
The International Monetary Fund estimates that about 40% of jobs worldwide are highly exposed to AI, rising to about 60% in advanced economies, against 40% in emerging markets and 26% in low-income countries. In advanced economies it expects roughly half of the exposed jobs to benefit from AI raising productivity, while in the other half AI could take over key tasks and reduce demand for workers.
Older automation research points the other way. The OECD’s 2023 Employment Outlook found that occupations at the highest risk of automation make up about 27% of employment across its member countries, and those were mostly low and middle skilled jobs. Generative AI changes that picture: it reaches office and professional work that earlier machines and software could not.
The careers growing fastest worldwide
The WEF’s Future of Jobs Report 2025 surveyed more than 1,000 employers with over 14 million workers in 55 economies. Two lists matter, because they answer different questions.
- Fastest growing by percentage: big data specialists, fintech engineers, AI and machine learning specialists, software and applications developers, and security management specialists lead the list. Green transition roles such as autonomous and electric vehicle specialists also appear in the top 15. These are small fields growing quickly from a low base.
- Most new jobs in total: farmworkers, delivery drivers, construction workers, shop salespeople and food processing workers add the most jobs, followed by the care economy (nurses, social workers and counsellors, personal care aides) and teachers. Demand here comes from growing populations, aging, and the build-out of homes, energy and infrastructure.
- Declining: clerical and secretarial jobs fall the most. Cashiers and ticket clerks, and administrative assistants and executive secretaries, lose the most jobs, while postal clerks, bank tellers and data entry clerks shrink fastest. Graphic designers have joined the declining list, a sign that generative AI is reaching creative work too.
Employers in the same survey expect about 39% of workers’ core skills to change by 2030. Even in a growing career, the job you do in five years will not look exactly like the job today.
Top careers and how much AI touches them
The AI exposure column borrows the U.S. Bureau of Labor Statistics’ August 2026 categories for 831 U.S. occupations. BLS combines theoretical exposure with observed AI interactions mapped to tasks; those interactions do not directly establish on-the-job use by each occupation. The regional labels below are the author’s approximate mappings to U.S. jobs, sometimes grouping several occupations, not locally measured ratings. Tasks, licensing, language, technology and adoption differ across countries. Consult the linked BLS table for the exact U.S. occupation; a grouped regional label is not an official BLS category. Exposure does not predict replacement, productivity, wages or adoption.
| Career | Outlook | AI exposure | What AI is likely to change |
|---|---|---|---|
| Registered nurses and nurse practitioners | Growing almost everywhere as populations age | High | Charting, triage notes and scheduling; the hands-on care stays human |
| Personal care and home health aides | Among the largest job gains worldwide | Moderate | Rotas and records; the physical care is hard to automate |
| Physician assistants and physical therapist assistants | Fast growth in the US | Low | Paperwork and documentation help |
| Electricians | In shortage across Europe; grid and data center demand | Moderate | Estimating, fault finding and compliance paperwork |
| Construction workers and carpenters | Large absolute job gains | Low | Planning and quoting; the building work itself changes little |
| Farmworkers | The largest absolute job gain in the WEF survey | Low | Machinery, sensors and forecasting rather than chatbots |
| Delivery and light truck drivers | Growing with online shopping | Moderate | Route planning; self-driving vehicles are a separate, slower risk |
| Software developers | Among the fastest-growing roles | Very high | Code is written and tested faster; the job shifts to design, review and integration |
| Data scientists and AI specialists | Fastest-growing group worldwide | Very high | They build the tools, while routine analysis gets automated |
| Information security specialists | Fast growth | Very high | AI helps defenders and attackers alike, which keeps demand up |
| Teachers | Growing worldwide in the WEF survey | High | Lesson planning and marking; teaching a room stays human |
| Accountants and financial managers | Steady to growing | Very high | Reconciliations, reports and first drafts of analysis |
| Customer service representatives | Falling in the US | Very high | Chatbots handle routine questions; people handle the hard cases |
| Data entry clerks, bank tellers and cashiers | Among the fastest declines | Very high or High | AI, self-service and automation take over much of the work |
| Graphic designers and writers | Flat to declining | Very high | First drafts and variations are generated; taste and judgment are what is paid for |
Two patterns stand out. First, high exposure and strong growth can go together: data scientists and software developers are among the most exposed occupations and still among the fastest growing, because AI raises demand for people who build and run it. Second, the jobs with the lowest exposure are mostly physical, licensed or hands-on care work, and many of them are already short of workers.
Who is most exposed
- Richer countries. The ILO puts generative AI exposure at 34% of employment in high-income countries against 11% in low-income countries, because richer economies have more office and professional jobs.
- Women. Women are more likely to work in clerical jobs. Globally, 4.7% of employed women are in the most exposed group against 2.4% of men; in high-income countries it is 9.6% against 3.5%.
- Graduates and office workers. Unlike earlier waves of automation, generative AI reaches professional work in finance, law, marketing and software. The IMF notes that college-educated workers are more exposed but also better placed to benefit.
Top careers by region
The global trends hold almost everywhere, but the details differ by country.
- United States: healthcare adds about a third of all new jobs to 2035, and BLS now rates every occupation for AI exposure. Nurse practitioners, data scientists and solar installers grow fastest.
- UK and Europe: doctors, nurses, care workers, building trades and welders are in the widest shortage, while clerical work is in surplus. UK finance and professional jobs are the most exposed to AI.
- India and Asia-Pacific: India’s tech services workforce is both the region’s biggest AI opportunity and its biggest exposure, Japan needs hundreds of thousands more care workers, and Australia expects AI to augment most jobs rather than automate them.
- Africa: farming and small businesses still employ most people in West and East Africa, the continent is short of millions of health workers, and AI exposure is low overall but high in the call centers, banks and offices of South Africa and North Africa.
- South America: most jobs are in services, a quarter to over a third could be touched by generative AI, and patchy internet access holds back many of the workers who could gain from it.
How to choose a career that holds up
- Think in tasks, not job titles. List what you actually do in a week. Tasks that are routine, screen-based and rule-driven are the ones AI absorbs first. Tasks that need judgment, trust, physical skill or a license last longer.
- Look for demand and exposure together. A growing field with high exposure, like software or data, rewards people who learn the tools. A shrinking field with high exposure, like data entry, is the one to plan an exit from.
- Consider relevant AI skills in your current job. Their value depends on tasks, employer needs, implementation and reliable use. Exposure research does not prove that AI users are always retained or promoted.
- Check the data for your own country. Shortage lists and official projections are published by most governments, and they change every year. The region guides link to them.
- Weigh the pay against the cost of getting there. A career change that needs years of training has a real price. The Real Hourly Wage calculator shows what a job pays once commuting and work costs are counted, and the Salary Comparison by Country tool compares pay across borders at local prices.
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Common questions
Which careers are safest from AI?
The least exposed careers are mostly hands-on, licensed or care work: physician assistants, physical therapist assistants, dental hygienists, construction trades, roofers, welders, power-line workers and nursing assistants are all rated Low by the US Bureau of Labor Statistics. Many of them are also in shortage, so demand is strong.
Which jobs is AI most likely to replace?
Routine clerical and administrative jobs face the most pressure. Data entry clerks, word processors, payroll clerks, bank tellers, telemarketers and administrative assistants are both highly exposed to AI and already among the fastest-declining occupations in the US and in the World Economic Forum’s global survey.
Will AI create more jobs than it destroys?
Employers surveyed by the World Economic Forum expect 170 million jobs to be created and 92 million displaced between 2025 and 2030, a net gain of 78 million, though not all of that change comes from AI. The new jobs often need different skills from the ones lost, so the gain does not help a displaced worker unless they can retrain.
Is AI exposure the same as job loss?
No. Exposure means AI can help with or complete some of a job’s tasks. The International Labour Organization expects most exposed jobs to be transformed rather than replaced, and some of the most exposed careers, such as data scientists and software developers, are among the fastest growing.
Related guides
Use these dated projections and source tables as starting points, not promises about an individual job. A shortage, unmet care need or projected occupation-wide increase is not necessarily a funded local vacancy. Check current local requirements, vacancies and training costs before committing to a career move.
Sources
- The Future of Jobs Report 2025, World Economic Forum
- Generative AI and Jobs: A Refined Global Index of Occupational Exposure (Working Paper 140), International Labour Organization
- Gen-AI: Artificial Intelligence and the Future of Work (Staff Discussion Note SDN/2024/001), International Monetary Fund
- OECD Employment Outlook 2023: Artificial Intelligence and the Labour Market, OECD
- Artificial Intelligence (AI) exposure categories, U.S. Bureau of Labor Statistics
- Employment Projections: 2025 to 2035 (news release), U.S. Bureau of Labor Statistics
This guide is for informational and educational purposes only. It is not financial, career, legal, or tax advice. Projections and AI exposure ratings describe occupations, not individual jobs, and can change as new data is published.
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