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Which US Jobs Are Most at Risk from AI in 2026?

The short answer: clerical and administrative workers, not programmers. Secretaries, customer service representatives, and office clerks all score 8.5/10 on AI exposure.

We scored all 341 occupations tracked by the US Bureau of Labor Statistics on AI exposure. Here is what the data shows about 143 million American workers and which roles face the most significant risk from AI in 2026.

Key findings

  • Clerical and administrative workers score 8.5/10 on AI exposure - the highest of any major group across 143 million US workers.
  • Over 16 million Americans work in the highest-risk occupations, including 3.4M secretaries, 2.8M customer service reps, and 2.6M general office clerks.
  • The average AI exposure across all 341 US occupations is 4.4/10 - meaning automation risk is moderate, not extreme, for most workers.
  • Managers and professionals face real AI exposure (5.5 and 6.5 out of 10) but their high wages and judgment requirements give them more protection than the data alone suggests.
  • The safest jobs involve physical presence, human care, and unpredictable environments - agriculture, skilled trades, and personal services score below 3/10.

The full picture: 143 million workers, 341 occupations

The US Bureau of Labor Statistics tracks employment across 341 detailed occupational categories covering every major sector of the economy. Using data from BLS, we scored each occupation on seven dimensions: AI exposure, robotics risk, offshoring risk, remote work potential, employment size, wage level, and projected 10-year growth.

AI exposure specifically measures how much of an occupation's core tasks can already be performed - or significantly augmented - by current AI systems. A score of 8.5/10 does not mean the job disappears tomorrow. It means a large proportion of the daily work is within reach of AI tools available right now in 2026.

143M
Total US workers tracked
4.4/10
Average AI exposure score
341
Occupations analyzed

The most AI-exposed occupations

Thirteen occupation groups score 8.5/10 - the highest level in our dataset. Every single one falls under the clerical and office support category. These are roles whose primary function is information handling: collecting, sorting, recording, and communicating structured data. That is precisely what large language models and AI automation tools do best.

# Occupation AI Score Workers Median Wage
1Secretaries and Administrative Assistants8.5/103,453,000$47,460
2Customer Service Representatives8.5/102,814,000$42,830
3General Office Clerks8.5/102,646,000$43,630
4Bookkeeping, Accounting and Auditing Clerks8.5/101,613,000$49,210
5Information Clerks8.5/101,337,000$43,730
6Material Recording Clerks8.5/101,301,000$46,120
7Financial Clerks8.5/101,193,000$48,650
8Receptionists and Information Clerks8.5/101,007,000$37,230
9Postal Service Workers8.5/10500,000$57,870
10Tellers8.5/10347,000$39,340
11Bill and Account Collectors8.5/10167,000$46,040
12Public Safety Telecommunicators8.5/10105,000$50,730
13Desktop Publishers8.5/105,000$53,620

Together these 13 occupation groups employ approximately 16.5 million Americans. That is one in every nine US workers. The median wage across this group sits around $45,000 per year - solidly middle-income, not the lowest-paid work in the country. These are stable, full-time jobs that many families depend on.

Why clerical workers and not programmers?

This surprises most people. Software developers and data analysts are also exposed to AI - they score 6.5/10 in our dataset. But there is a critical difference: programmers use AI as a productivity multiplier, while clerical workers face AI as a task replacement.

A software engineer using GitHub Copilot writes more code faster. They remain employed and often more valuable. A customer service AI system handles the entire call without a human in the loop at all. The nature of the displacement is fundamentally different.

Clerical roles are also characterised by high volume, low variance tasks. They process the same types of requests repeatedly, follow established rules, and communicate in predictable patterns. AI systems trained on millions of similar interactions can match or exceed human performance on exactly these tasks.

The professionals: high exposure, high protection

The second-highest scoring major group is professionals - accountants, analysts, lawyers, and knowledge workers - at 6.5/10. This group employs around 43 million Americans and earns a median of $82,031 per year.

The high exposure reflects the reality that AI tools can already draft legal documents, produce financial analyses, write code, and summarise research. But high wages signal that employers pay a premium for judgment, client relationships, accountability, and the ability to handle novel situations. AI augments this work rather than replacing the worker entirely - at least for now.

Managers score 5.5/10 - the same as plant and machine operators. The similarity is superficial. Managers earn $115,056 median annually. Their exposure comes from AI handling administrative and analytical tasks within management. Their protection comes from accountability, organisational relationships, and decision-making in complex, human environments.

The safest jobs from AI

At the bottom of the AI exposure scale are occupations that require physical presence in unpredictable environments, direct human care, or highly specialised manual skills.

Occupation Group AI Score Workers Median Wage
Skilled Agricultural Workers2.0/103,847,000$37,020
Craft and Related Trades Workers2.5/1011,215,000$56,006
Plant and Machine Operators3.0/1018,757,000$45,844
Service and Sales Workers3.5/1029,101,000$40,200

Electricians, plumbers, carpenters, and HVAC technicians score 2.5/10. They work in physical environments that change from job to job, require fine motor skills honed over years of practice, and solve problems that cannot be fully anticipated. A robot that could do this work reliably across all environments does not exist at scale in 2026.

Agricultural workers score just 2.0/10 for similar reasons - field conditions, crop variation, and physical dexterity in unstructured environments. Interestingly, their wages ($37,020 median) are lower than many high-AI-exposure clerical workers, which illustrates that AI exposure and wage level do not always align with economic risk.

What this means for you

If you work in an 8.5/10 occupation, this does not mean you lose your job tomorrow. It means the tasks you do today are increasingly within reach of AI systems, and employers will start asking whether they need the same headcount to produce the same output. The realistic timeline for significant displacement in clerical work is 3 to 7 years, not months.

The most practical response is to understand which parts of your role require judgment, relationships, and accountability - and lean into those. The workers who survive and thrive in high-AI-exposure roles are the ones who use AI tools themselves, handling more complex cases rather than the routine ones AI takes over.

If you are choosing a career or considering a change, the data suggests trades and care work are the most durable choices in terms of AI displacement risk. Electricians earn more than customer service representatives, face lower automation risk, and are in short supply. That combination rarely exists elsewhere in the labour market.

Explore the live data for any occupation

See AI exposure, wages, robotics risk, and job growth for all 341 US occupations - or compare across 206 countries.

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Methodology

Employment figures are from the US Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) programme, most recent available data. AI exposure scores are research-based estimates per ISCO-08 occupation group, informed by Frey-Osborne, OECD, and IMF studies on task-level automation susceptibility. Scores reflect the proportion of an occupation's core tasks that current AI systems can perform or significantly augment. They are not predictions of job loss rates.

Frequently asked questions

Which US job is most at risk from AI in 2026?
Secretaries and administrative assistants have the highest AI exposure score at 8.5/10, employing 3.4 million Americans. Customer service representatives (2.8 million workers) and general office clerks (2.6 million workers) are equally exposed at 8.5/10. All three roles involve high-volume, routine information handling that AI can replicate effectively.
Will AI replace customer service jobs?
Customer service representatives score 8.5/10 on AI exposure. AI systems already handle a substantial share of routine customer inquiries across banking, retail, and telecoms. However, complex complaints, escalations, and relationship-sensitive interactions still require human judgment. The most likely outcome over the next 5 years is significant headcount reduction in routine tier-1 support, with remaining workers handling more complex cases.
Are programmers at risk from AI?
Software developers score 6.5/10 on AI exposure, which is high but not at the top of the scale. The key distinction is that AI tools like code assistants make programmers more productive rather than replacing them outright. Demand for software development remains strong and growing. The risk is more about the number of developers needed per project declining, rather than the profession disappearing.
What jobs are completely safe from AI?
No occupation scores 0/10 - AI has some potential impact across all work. The closest to fully safe are skilled trades (electricians, plumbers, carpenters) at 2.5/10 and agricultural workers at 2.0/10. These roles require physical dexterity in variable environments, and the robotics needed to automate them at scale does not exist yet for most settings.
How many US jobs are at high risk from AI?
Based on our scoring, occupations with an AI exposure score of 7 or above cover approximately 16.5 million US workers - around 11.5% of the 143 million workers in our dataset. This group is concentrated in clerical and administrative support roles.
Where does this data come from?
Employment and wage data comes from the US Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics programme. AI exposure scores are derived from research-based estimates per ISCO-08 occupation group, informed by studies from Frey-Osborne (Oxford), the OECD, and the IMF. All data is freely available to explore at worldjobsdata.com.