Find Out Which Careers Are at Risk and What You Can Do Next
AI is changing the workforce. Will your job survive?
Our website will track which jobs are most at risk and what to do next.
Advances in artificial intelligence (AI) and robotics are automating many tasks, raising concerns about large-scale job displacement (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics) (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Certain industries and job functions are especially vulnerable. Routine, repetitive jobs – both manual and cognitive – face the highest risk. For example:
Manufacturing & Warehousing: Industrial robots can assemble products and handle materials around the clock. Companies like Foxconn have already replaced ~60,000 factory workers with robots (CLSA, WEF, and Citi on the Future of Robots and AI in the Workforce - Business Insider). Amazon uses over 100,000 warehouse robots (Kiva machines) to move goods, boosting output and reducing reliance on human pickers (7 Industries That Will Be Taken Over by AI and Robots (And How to Adapt) | Datafloq).
Transportation (Driving): Self-driving technology threatens driving jobs. Autonomous trucks and taxis are being piloted; by 2030, 50–70% of truck driver roles could be automated according to some projections (Self-Driving Trucks – Timelines and Developments) (The Dawn of Autonomous Trucking: Navigating the Evolving ...). Ride-hailing and delivery services are also testing driverless vehicles.
Retail & Food Service: AI-driven kiosks and self-checkouts are replacing cashiers and clerks. McDonald’s rolled out self-order kiosks and tested AI drive-thru voice assistants to reduce staff (7 Industries That Will Be Taken Over by AI and Robots (And How to Adapt) | Datafloq). Many supermarkets now have self-checkout machines, and some stores (like Amazon Go) use computer vision to eliminate checkout entirely. Fast-food kitchens are experimenting with robotic cooks and beverage dispensers for tasks like flipping burgers or mixing drinks.
Clerical & Administrative Work: Software “bots” and generative AI can handle data entry, basic accounting, and documentation. Tools like ChatGPT can draft emails, reports, and even code, threatening roles in data processing and junior programming (Companies That Have Replaced Workers with AI in 2024 & 2025). Major employers are acting on this – for instance, IBM announced plans to replace ~30% of its back-office roles (about 7,800 jobs) with AI in the next 5 years (Companies That Have Replaced Workers with AI in 2024 & 2025). Banks are likewise exploring AI to automate entry-level analyst work (e.g. data input and report generation) (Companies That Have Replaced Workers with AI in 2024 & 2025).
Customer Service & Call Centers: AI chatbots and voice assistants are increasingly handling customer inquiries. Companies like BT (British Telecom) are cutting thousands of customer service jobs in favor of AI bots (Companies That Have Replaced Workers with AI in 2024 & 2025), and many banks and airlines use AI-powered phone menus and online chatbots to resolve common requests. Generative AI (like ChatGPT) can provide 24/7 customer support, answer FAQ, and even upsell products, reducing the need for large call-center teams (Companies That Have Replaced Workers with AI in 2024 & 2025) (Companies That Have Replaced Workers with AI in 2024 & 2025).
Key AI/Robotic Technologies driving this automation include large language models (e.g. ChatGPT) for text, speech, and code tasks; computer vision systems for visual inspection and checkout-free stores; machine learning algorithms that can make decisions (loan approvals, scheduling, etc.); and physical robots or cobots (collaborative robots) for material handling, assembly, and transportation. Autonomous vehicles, warehouse robots, drone delivery, robotic process automation (RPA), and AI software agents are all replacing or reducing human labor in various domains. For instance, AI-powered software now assists in medical imaging and legal document review – tasks once done exclusively by radiologists or paralegals – augmenting productivity and sometimes obviating junior roles (Companies That Have Replaced Workers with AI in 2024 & 2025).
The speed of AI adoption is accelerating. Globally, the number of industrial robots has doubled in the last 7 years, reaching about 3.9 million in operation (Which Countries Have the Most Industrial Robots?). In manufacturing, robot density (robots per 10,000 workers) hit a record high in 2022. Asia leads: South Korea now has 1,012 robots per 10,000 manufacturing workers, vs. about 285 per 10,000 in the U.S. (Which Countries Have the Most Industrial Robots?). 73% of companies surveyed plan to adopt automation by 2025 (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). The World Economic Forum forecasts that worldwide, 85 million jobs could be displaced by AI/automation by 2025 (with 97 million new tech-driven jobs created) (Recession and Automation Changes Our Future of Work, But There ...). In the U.S., studies estimate ~25% of jobs across the economy have high potential for automation by the early 2030s (Generative AI and the future of work in America | McKinsey). However, job impact will vary widely by role and region, as discussed below.
Certain occupations employing millions of Americans are highly susceptible to replacement by AI and robots, especially those involving routine physical work or repetitive information processing. Below is a ranked list of the 20 jobs most at risk, by U.S. employment size (largest first), with estimates of how many people hold these jobs and how soon automation could significantly affect them:
(image) Top at-risk jobs by number of U.S. workers (in millions). Roles like retail salesperson (~4.3M workers) (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics), fast-food counter worker (~4.0M) (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics) and cashier (~3.6M) (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics) employ some of the largest labor forces and are increasingly automatable. Even clerical roles such as bookkeeping clerks still account for ~1.7M jobs ( Bookkeeping, Accounting, and Auditing Clerks : Occupational Outlook Handbook: : U.S. Bureau of Labor Statistics), making their potential displacement economically significant.
Retail Salespersons – ~4.3 million employed. (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics) Automated checkout technologies, e-commerce, and AI-driven inventory systems are reducing demand for in-store retail staff. Many cashier tasks are being bundled into the sales role or eliminated by self-checkout (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Timeline: Ongoing – gradual declines through 2030 as online shopping grows and stores use fewer sales associates per customer.
Fast Food and Counter Workers – ~4.0 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Fast-food jobs (taking orders, food prep) are being automated by self-service kiosks, mobile ordering apps, and kitchen robots. Several chains are piloting robotic fry cooks and automated beverage machines. Timeline: Significant automation within 5–10 years, especially for ordering and simple food prep, as technology becomes cheaper for franchise owners.
Cashiers – ~3.6 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Self-checkout stations, AI-powered retail, and “cashier-less” store concepts (Amazon Go, etc.) directly cut cashier positions. Timeline: Rapid – many grocery and retail stores already shifted a large share of transactions to self-checkout in the last few years. Expect > +50% of cashier tasks automated by late 2020s, with role largely phased out in many stores by 2030 (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics).
Customer Service Representatives – ~3.0 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Call centers and support desks can use AI chatbots and voice agents to handle routine inquiries. One study found over 30% of tasks in customer service could be done by generative AI tools by 2025 (Companies That Have Replaced Workers with AI in 2024 & 2025). Timeline: Accelerating now – within 5 years AI could handle the bulk of Tier-1 support questions, though human reps may remain for complex issues or irate customers.
Laborers and Freight/Stock Movers – ~3.0 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). These general warehouse/stockroom labor jobs involve moving goods, packing, loading trucks – tasks suited to robotics and automated guided vehicles. Amazon’s warehouses, for example, use robots to bring shelves to human pickers, greatly reducing walking labor. Timeline: Ongoing – incremental automation each year; by 2030, large warehouses and distribution centers could be highly robotized, needing far fewer human loaders.
Administrative Assistants and Secretaries – ~2.5 million. Routine office support duties (scheduling, data entry, basic bookkeeping, form-filling) can be handled by software. Digital calendars and AI email responders reduce the need for human assistants. Timeline: Steady attrition – already these roles are in decline (The Future of Jobs Report 2025 | World Economic Forum); expect continued AI-driven reduction over the next decade, especially for executive assistant and general secretary positions not requiring on-site tasks.
General Office Clerks – ~2.5 million ([PDF] Occupational Employment and Wages - May 2023). This category includes clerical workers who do filing, transcription, and administrative tasks across offices. Much of their work (record-keeping, information lookup, simple reports) is being digitized. Timeline: Moderate – BLS projects a decline in office clerk jobs through 2033 despite economic growth (General Office Clerks : Occupational Outlook Handbook). Many tasks have already been computerized; remaining clerks may see job opportunities dwindle ~5%+ each decade.
Janitors and Cleaners – ~2.3 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Autonomous cleaning robots (robot vacuums, floor scrubbers) are beginning to handle basic cleaning in offices, stores, and hospitals. Large retailers use robotic floor cleaners at night. Timeline: Slow-moderate – basic cleaning bots are here, but human janitors still handle complex tasks. Over the next 10 years, expect modest job impact; robots might handle 20–30% of floor cleaning by 2030 in big facilities, but humans still needed for detailed cleaning and upkeep.
Waiters and Waitresses – ~2.2 million. Front-of-house restaurant service is somewhat protected by the human touch, but automation is encroaching. Many restaurants let customers order via tablet or phone app, reducing waitstaff needed to take orders. Some are testing robot “food runners” to deliver dishes to tables. Timeline: Slow – by late 2020s, routine order-taking might be mostly self-service at major chain restaurants, but full replacement of waitstaff is unlikely since diners value human servers for hospitality. Expect gradual reduction in staff per restaurant rather than complete automation.
Stockers and Order Fillers – ~2.1 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). These workers pack inventory on shelves or compile orders in e-commerce warehouses. Automated storage and retrieval systems (ASRS) and warehouse robots can now handle a lot of item picking and restocking, especially for standard-shaped goods. Timeline: Ongoing – warehouses are already seeing rapid robot adoption; by 5–7 years many fulfillment centers will be heavily automated. Store shelf-stocking by robots is slower to catch on (aside from experimental robots that scan for out-of-stock items), so grocery and retail stocker jobs may persist a bit longer.
Heavy Truck and Tractor-Trailer Drivers – ~2.0 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Long-haul trucking is a highly-prominent automation target with self-driving trucks. Several companies (Waymo, Tesla, TuSimple) are testing autonomous semis on highways. Timeline: Medium-term – by 2030, autonomous trucks may begin handling point-to-point highway driving on select routes (Will autonomy usher in the future of truck freight transportation?), displacing some driver miles (while humans focus on last-mile and local haul). Large-scale job loss may come in the 2030s if regulation permits driverless freight nationwide.
Bookkeeping, Accounting, and Auditing Clerks – ~1.66 million ( Bookkeeping, Accounting, and Auditing Clerks : Occupational Outlook Handbook: : U.S. Bureau of Labor Statistics). Accounting software and AI have dramatically reduced demand for manual bookkeeping. Tasks like invoice processing, expense tracking, and basic payroll are now often automated in software (e.g., QuickBooks, SAP). Timeline: Ongoing – this occupation has been declining for years (The Future of Jobs Report 2025 | World Economic Forum). Expect a further ~5%+ drop in the 2020s as small businesses fully adopt digital accounting and AI handles more reconciliation and reporting tasks.
Receptionists and Information Clerks – ~1.1 million. Front-desk receptionists greet visitors and handle phone calls – functions partially replaced by automated phone directories, sign-in kiosks, and digital assistants. Many offices now use phone menu systems or virtual reception apps to route calls. Timeline: Gradual – while receptionist employment is projected to slightly decline in the coming decade (–0.5% by 2032) (The job market for receptionists in the United States - CareerExplorer), humans will likely remain in many front-desk roles for the personal touch. Expect slow erosion as more businesses use technology for initial customer contact.
Manufacturing Production and Assembly Workers – ~1.0 million. This includes factory assemblers, machine operators, and welders. Industrial robots are highly prevalent in automotive and electronics assembly, performing welding, painting, and repetitive assembly. Timeline: Advanced manufacturing has been automating for decades; the trend continues. Simple, repetitive assembly jobs are mostly gone or will be by 2030. Remaining manufacturing roles often involve supervising machines or doing custom assembly – those might last longer, but overall manual assembly jobs will keep declining.
Farm Workers (Crop Field Laborers) – ~0.9 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). Agriculture employs many seasonal laborers for planting and harvesting. Automation here has lagged, but new agri-tech is emerging: robotic strawberry pickers, drones for crop monitoring, autonomous tractors for plowing and weeding (). Timeline: Slow in short term – given technological and cost hurdles, most U.S. farm work in the next 5 years will still be manual. However, by the mid/late 2030s, widespread use of farm robots could begin displacing a significant share of field labor (especially as equipment costs drop and if labor remains scarce).
Paralegals and Legal Assistants – ~0.34 million (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). These roles involve a lot of document preparation, basic research, and form completion. AI legal tools can now review contracts, find case precedents, and even draft legal documents. Law firms are adopting e-discovery AI that accomplishes in minutes what teams of paralegals did in weeks. Timeline: Medium – paralegal hiring is slowing as these tools improve. Complex tasks and client interaction still need humans, but entry-level legal support roles could shrink significantly by 2030 as AI handles more administrative legal work.
Bank Tellers and Related Clerks – ~0.45 million. The number of bank tellers has been falling due to ATMs, online banking, and mobile apps. Routine transactions (deposits, withdrawals, balance inquiries) are now done without a human. Banks are shifting remaining tellers toward advisory roles or closing branch locations. Timeline: Ongoing – teller jobs are projected to continue declining; by 2030 this occupation may be a fraction of its former size (41% of companies worldwide plan to reduce workforces by 2030 ...). (WEF ranks bank tellers among the fastest-declining jobs globally (41% of companies worldwide plan to reduce workforces by 2030 ...).)
Postal Service Mail Sorters and Clerks – (under 0.2 million). Mail sorting and processing has been highly automated with machines for decades. Now even customer-facing postal clerks (at counters) are at risk as postal services offer self-service kiosks and more people buy postage and labels online. The U.S. Postal Service has trimmed staff via automation and volume declines. Timeline: Rapid decline – postal clerk jobs are expected to shrink fast as snail-mail volume drops and automation improves. WEF identifies postal clerks as the #1 fastest-declining role worldwide to 2030 (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog) (The Future of Jobs Report 2025 | World Economic Forum).
Data Entry Keyers – (very small and shrinking). Once a common clerical job, pure data entry (typing information into systems) has largely been automated or offshored. Scanning tech, OCR (Optical Character Recognition), and digital workflows capture data at the source, eliminating many manual typing roles. Timeline: Largely complete – this job category has already decreased drastically. By the mid-2020s, data entry clerks will be extremely niche (only needed for specialized tasks or in smaller markets that haven’t modernized).
Telemarketers – (~0.14 million). Robocalling systems and voice AI can make hundreds of sales calls per hour, drastically cutting demand for human cold-callers. Consumers are also averse to live telemarketing and often let calls go to automated messages. Timeline: Near complete – automated dialers and recorded pitches have largely taken over. Telemarketing as a human job is disappearing (down ~50% in the 2010s (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics)), and by 2030 it’s likely to be almost entirely an AI/automated endeavor for routine sales calls. (Notably, telemarketer is ranked among the top 15 declining jobs by WEF) (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog).
Sources: Employment figures are from U.S. Bureau of Labor Statistics (2018–2023 data) and job decline outlooks draw on BLS projections and World Economic Forum forecasts (The Future of Jobs Report 2025 | World Economic Forum) (Growth trends for selected occupations considered at risk from automation : Monthly Labor Review: U.S. Bureau of Labor Statistics). As seen, many vulnerable jobs are low to mid-skill roles with highly repetitive duties, which technology can replicate. The expected automation timeline varies: some roles (e.g. data entry, telemarketing) are already largely automated, whereas others (like trucking or fast-food cooking) are just beginning to see effective automation and will have a more gradual impact over this decade.
On the other end of the spectrum, certain jobs remain relatively safe from automation. These typically require qualities like human judgment, emotional intelligence, complex problem-solving, creativity, and dexterity in unstructured environments – areas where AI and robots currently struggle (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University) (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Below is a ranked list of 20 occupations that experts consider least likely to be replaced, and why they are resistant to automation. We also include their typical salaries and growth outlooks to highlight career prospects:
Healthcare Professionals (Doctors, Nurses, etc.) – Healthcare roles demand critical thinking, hands-on skills, and empathy that AI cannot replicate (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). A doctor must synthesize a patient’s history, symptoms, and emotional state – tasks aided by AI diagnostic tools but ultimately requiring human judgment and trust. Nurses provide compassion and adapt in unpredictable situations, from calming a scared patient to responding to sudden complications. These human elements keep such jobs safe. Median Salary: Registered Nurses ~$86,000/year (RN Salary 2024 (RN Salaries by State & Workplace)); Physicians often $200k+ (varies by specialty). Outlook: Growing. RN employment is projected +6% (2021–2031) (RN Salary 2024 (RN Salaries by State & Workplace)) due to an aging population. Demand for doctors and nurse practitioners is also rising (NPs are one of the fastest-growing jobs at +40% projected (The Future of Jobs Report 2025 | World Economic Forum)).
Teachers and Educators – Teaching is a deeply human endeavor requiring emotional intelligence, adaptability, and mentorship. While online learning and AI tutors can supplement education, good teachers inspire and personalize learning in ways technology can’t (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). They manage classroom dynamics, provide socio-emotional support, and adjust methods on the fly when students are struggling – nuanced skills that defy full automation. Median Salary: High school teachers ~$62,000/year (High School Teacher Career Profile - Truity). Outlook: Stable/Growing. Projected 5% growth for high school teachers (2021–2031) (about average) as student populations hold steady. Demand is higher in specialties like special education and for post-secondary educators (+8%) (Postsecondary Teachers : Occupational Outlook Handbook) (Postsecondary Teachers : Occupational Outlook Handbook).
Creative Professionals (Writers, Artists, Designers) – Creativity remains a relative weak spot for AI. Human creators infuse originality, cultural context, and emotional depth into their work (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). AI can generate boilerplate content or imitate styles based on existing data, but it struggles with truly novel ideas or resonating on a deep human level. For instance, marketing teams use AI to draft copy, but human creatives refine it into compelling stories and branding (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University) (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Similarly, while AI art generators exist, artists who create new genres or authentic personal expressions remain in demand. Median Salary: Varies widely. e.g. Writers ~$69k, Graphic Designers ~$50k. Top creatives (art directors, authors, etc.) can earn much more. Outlook: Mixed but generally resilient. Routine design jobs may be augmented by AI, but roles requiring high creativity and conceptualization (creative directors, UX designers) are growing with the digital economy. The need for original content and design actually grows as automation produces more generic output – human creativity becomes the differentiator.
Social Workers and Counselors – These roles center on human connection, listening, and guidance through personal challenges. Empathy, trust-building, and ethical judgment are core to social work and therapy, which AI cannot emulate beyond surface-level prompts (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Clients often seek the human rapport and emotional support that come from a trained counselor or social worker. They must interpret unspoken cues, adjust approaches for each individual’s complex life situation, and sometimes make tough ethical decisions – all requiring human sensitivity. Median Salary: Social Workers ~$50,390; Mental health counselors ~$48,520 (May 2021 data). Outlook: Faster than average growth. e.g. +9% for social workers (2021–2031) as demand for health and family services grows. Counseling fields (substance abuse, behavioral disorders) are projected to grow ~22% this decade due to greater attention to mental health.
Sales Professionals (Complex & Relationship-Based Sales) – While AI can handle routine sales (e.g. simple e-commerce transactions), many sales roles rely on building relationships and understanding nuanced customer needs. Enterprise sales, consulting sales, and any high-value deal-making remain human-intensive. Top salespeople read body language, build trust, negotiate creatively, and persuade – skills beyond AI. As one sales coach notes, AI can analyze call transcripts and suggest improvements, but “the human touch is essential for closing deals.” (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University) (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Median Salary: Sales roles vary. Corporate sales representatives ~$62k; Sales managers ~$127k. Outlook: Stable. Automation handles lead-gen and transactional selling, but demand remains for skilled sales reps in B2B, real estate, pharma, etc. (These roles often have performance-based pay – top performers earn well above median).
Legal Roles (Lawyers, Judges) – Lawyers must interpret laws, craft nuanced arguments, and make ethical judgments. Much of law is gray-area reasoning and advocacy, which AI cannot do with human-level nuance (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). A lawyer or judge weighs precedent against unique case facts, considers societal values, and negotiates settlements – all requiring human insight and responsibility. AI tools help with document review and legal research, but cannot replace the strategic thinking and interpersonal negotiation done by attorneys in court or deal-making (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Judges, as arbiters of justice, also require a human moral compass. Median Salary: Lawyers ~$146,000/year (Lawyers : Occupational Outlook Handbook - Bureau of Labor Statistics). Outlook: Steady. Projected 5% growth (2023–2033) for lawyers (Lawyers : Occupational Outlook Handbook - Bureau of Labor Statistics). Certain legal support tasks will automate, but lawyer jobs themselves are expected to rise modestly with population and business growth.
Ethical Decision-Makers (Policy Makers, Regulators, Compliance Officers) – Roles that involve setting policies, making ethical decisions, or upholding social values are inherently human. For example, politicians and senior public officials must weigh trade-offs, respond to constituent needs, and maintain public trust – tasks far outside AI’s domain (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Similarly, compliance officers interpret ambiguous regulations and ensure a company’s actions align with legal and ethical standards. These jobs require a moral compass, accountability, and often a public mandate, none of which can be delegated to algorithms. Median Salary: Compliance Officers ~$72k; Elected officials – varies (often modest base salary but with influence/prestige). Outlook: Stable. Governance and regulatory roles will continue as long as society needs human accountability for decisions. AI will be a tool for analysis, but humans will make the judgments.
Mental Health Professionals (Psychologists, Psychiatrists) – Treating mental health relies on deep human connection and trust. Patients are often unwilling to confide in a machine about their innermost feelings. Therapists provide empathy, tailored therapy techniques, and the human warmth needed for healing (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). While apps and AI chatbots (like Woebot) can offer CBT exercises or check-ins, they lack the genuine rapport and adaptive emotional support a human psychologist provides. Psychiatrists similarly blend medical knowledge with understanding a patient’s psyche in ways beyond an AI’s capacity. Median Salary: Psychologists ~$81,040; Psychiatrists ~$208,000+ (physician level). Outlook: High Demand. Mental health awareness is growing; psychologist jobs projected +6% and therapists +22% (for substance abuse and mental health counselors) this decade, indicating strong need for humans in these roles despite digital tools.
Skilled Tradespeople (Electricians, Plumbers, Mechanics) – Trades jobs involve physical dexterity, on-site problem solving, and adaptability to unique situations (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). A plumber or electrician works in varied environments (different houses, tight crawl spaces, older buildings with surprises) and improvises solutions – tasks robots struggle with. These roles also require years of craft knowledge and often licensure. So far, automation in these fields is minimal; if anything, there’s a shortage of tradespeople in the U.S. (The critical demand for trade skills in the US | McKinsey). For example, fixing a complex electrical issue in a building or repairing an engine involves troubleshooting and manipulating tools in ways no robot can fully do. Median Salary: Electricians ~$60,040; Plumbers ~$59,880; Industrial Machinery Mechanics ~$59,380 (May 2021). Outlook: Very strong. Many trades face worker shortages and are projected to grow (Electricians +7%, 2021–2031; HVAC mechanics +5%). Retirements are creating extra demand (The critical demand for trade skills in the US | McKinsey). These jobs are “future-proof” not only against AI, but also recession-resistant and well-paid due to skilled labor scarcity.
Investigative Journalists and Broadcasters – Journalism that involves investigation, in-depth reporting, or live presenting remains hard to automate. Can you imagine a robot interviewing a source or a AI news anchor humans trust? Live reporters and hosts bring personal charisma, credibility, and the ability to react in real-time to events (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Investigative journalists build networks of contacts, dig through leads that aren’t neatly in databases, and exercise judgment about what information to publish – these tasks require human intuition and bravery (especially in speaking truth to power). Median Salary: Journalists ~$48,370; Broadcast Announcers ~$49,300. Top reporters or TV anchors can earn six-figure salaries. Outlook: Mixed. Overall journalist jobs have declined with media consolidation, but investigative journalism and multimedia content creation are still valued. Many outlets use AI to draft basic news briefs, but rely on human journalists for analysis, investigative pieces, and on-air roles.
Event Planners and Wedding Organizers – Coordinating large events involves creativity, crisis management, and intense people skills. Clients entrust planners with important personal or corporate occasions (weddings, conferences), and expect a human to handle last-minute issues or unique requests (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Event planners juggle vendors, solve unexpected problems (like weather or equipment failures), and tailor the experience to human preferences – a level of flexibility and personal touch AI can’t match. As one might quip, no one wants a robot to plan their daughter’s wedding or a VIP gala without human oversight. Median Salary: Meeting/Event Planners ~$49,470. Outlook: Good. Projected 18% growth (2021–2031) for meeting and event planners as businesses and individuals continue to value expertly orchestrated in-person experiences. Technology helps with logistics, but human planners remain in charge.
Performers and Entertainers (Actors, Musicians, Dancers, Models) – The performing arts thrive on uniquely human creativity and expression. Audiences connect with the emotion and spontaneity of human performers in concerts, theater, and on screen (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). While AI can generate music or even deepfake an image of an actor, it lacks the live presence and ability to truly engage an audience’s emotions in real time. Actors bring interpretation to roles that AI can’t; dancers and musicians physically embody art in ways machines cannot replicate. Even if a CGI character is on screen, it’s often voiced or performance-captured by a human. Median Salary: Varies extremely (many struggling artists vs. megastars). e.g. Actors ~$46,960 median (with a wide range), Singers/Musicians ~$NA (often gig-based pay). Outlook: Stable. Entertainment consumption is higher than ever (streaming, live events). New AI effects might change some production techniques, but demand for human entertainers and the value of authenticity is not going away.
Veterinarians and Animal Trainers – Working with animals requires empathy, observational skills, and hands-on care. Pets and livestock can’t communicate issues directly; a vet must diagnose through experience and subtle cues – something AI can assist with (through pattern recognition in lab results, for instance) but not do alone. Animal training (for service animals, entertainment, or behavior correction) similarly needs patience, intuition, and adaptation to each animal’s temperament (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Robots aren’t trusted to care for beloved pets or manage unpredictable animal behavior. Median Salary: Veterinarians ~$100,370; Animal Trainers ~$31,280. Outlook: Growing. Vet jobs +19% (2021–2031) as pet ownership rises and more advanced veterinary care becomes common. Animal care fields overall are on the rise – one sign that human-animal interactions remain valued and require a human touch.
Personal Appearance Specialists (Hairstylists, Makeup Artists, Tattoo Artists) – These jobs combine artistry with personal service. Clients often develop loyalty to a favorite stylist or barber because of the human connection and trust involved (it’s someone’s appearance, after all). While a robot might technically cut hair, it lacks the consultative dialogue (“How do you want your hair?”) and the finesse to adjust styles based on face shape, fashion trends, and customer personality (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Likewise, makeup application for events or tattooing skin requires careful handcraft and understanding of human preferences. Median Salary: Hairdressers ~$29,670 (with top stylists in high-end salons earning much more); Makeup artists (theatrical) ~$134,750 (highly specialized). Outlook: Steady. Beauty services are expected to grow with population. These roles are hands-on and personalized – automation here is more sci-fi than imminent reality.
Business Strategists and Managers – High-level business roles (strategists, CEOs, project managers) involve big-picture thinking, leadership, and decision-making under uncertainty. AI can provide data, but humans still make the strategic calls (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Developing a business strategy requires synthesizing market trends, internal team capabilities, and a vision – a creative, human process. Managers also motivate teams, resolve conflicts, and provide mentorship. Those “soft” leadership skills are inherently human. As one analysis notes, AI can crunch numbers but doesn’t have the “leadership and social influence” that employers prioritize (The Future of Jobs Report 2025 | World Economic Forum) (The Future of Jobs Report 2025 | World Economic Forum). Median Salary: Business Operations Managers ~$98,000; Top Executives $179,520. Outlook: Strong. Good managers are in demand across industries. The Future of Jobs survey actually found leadership to be a growing skill even in the AI era (The Future of Jobs Report 2025 | World Economic Forum) (The Future of Jobs Report 2025 | World Economic Forum). Rather than replace leaders, AI will be a tool for them – making these roles even more critical to interpret AI insights and guide organizations.
Emergency First Responders (Firefighters, Paramedics, Police) – In emergencies, we rely on human heroes. Running into a burning building or providing CPR to a patient requires split-second physical reactions and courage that no current robot possesses. Firefighters also use judgment on how to attack a fire and adapt if conditions change (wind shifts, structural collapse) – real-world complexity that AI can’t handle autonomously. Paramedics make quick medical decisions in uncontrolled environments (roadside after an accident, etc.), showing creativity and compassion under pressure. While robots and drones can assist (e.g. firefighting drones, bomb squad robots), they are tools controlled by humans. Median Salary: Firefighters ~$50,700; EMTs/Paramedics ~$36,930. Outlook: Steady/Growing. These roles are expected to grow (~5–7% for EMTs/paramedics) or hold stable. Human responders will continue to be the front line in public safety for the foreseeable future.
Engineers and Scientists (Research & Development) – Engineers (civil, mechanical, etc.) design and oversee projects that often present unique challenges (every bridge or product can have custom requirements). They apply creative problem-solving and domain expertise to innovate – something AI cannot do independently. Similarly, scientists form hypotheses and design experiments to advance knowledge. While AI aids analysis, it cannot replace human curiosity and the scientific method. Also, many engineering tasks involve site-specific decision making and supervision (e.g. a civil engineer adapting plans during construction due to unexpected soil issues). Median Salary: Software Developers ~$132,000 (Software Developers, Quality Assurance Analysts, and Testers) (very high demand); Civil Engineers ~$88,050. Outlook: Excellent. Engineering and science occupations are growing (software devs +25% projected (The US Bureau of Labor Statistics predicts a 25% increase ... - Reddit), biomedical engineers +10%, environmental scientists +5% etc.). Rather than being threatened by AI, these roles are often creating and leveraging AI, and remain critical for innovation.
Culinary Chefs and Sommeliers – The culinary arts involve creativity and sensory experience that automation finds difficult. Top chefs experiment with flavors, textures, and presentation – an art and science merged with cultural trends and personal flair. Robots can follow recipes but not invent new ones with genuine inspiration. Tasting and adjusting seasoning is a human skill; even an AI-driven cooking machine can’t truly taste. Sommeliers (wine experts) similarly use a refined palate and interpersonal skills to recommend pairings to diners. A machine might analyze chemical compounds of wine, but it can’t replace the story and experience a sommelier provides (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Median Salary: Chefs ~$50,160 (though executive chefs in high-end restaurants earn far more); Sommeliers ~$62,000 (varying widely). Outlook: Good for high-end skills. Restaurant cooks as a category are not highly paid and face some automation at fast-food level (e.g. burger robots), but creative chefs remain in demand especially as the dining public continually seeks new cuisines and experiences. The rise of foodie culture means talented human chefs are highly valued.
Real Estate Agents and Home Inspectors – Buying or selling a home is a high-stakes, personal process. Most people want a human agent to guide them – someone who understands their needs and can build trust. Real estate transactions involve complex negotiations and emotional decisions, which a human is better at navigating (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Agents also add value through local market knowledge and networking. While property listing sites have automated some aspects (online listings, virtual tours), the “last mile” of closing a deal often relies on human persuasion and reassurance. Home inspectors similarly provide expert judgments on property conditions that buyers trust (and they often have to explain issues in person). Median Salary: Real Estate Agents ~$48,770 (with commission-based potential far above that for successful agents); Home Inspectors ~$61,640. Outlook: Steady. The real estate industry is adapting tech, but agents remain central. In 2022, ~90% of buyers used an agent despite online tools – indicating this people-centric job is here to stay.
Humanitarian Aid Workers and Caregivers – Roles focused on caring for others – whether in global crisis zones or in day-to-day personal care – remain extremely hard to automate. Humanitarian workers in the field make judgment calls in chaotic environments, coordinate with communities, and provide compassion to people in distress (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University). Their work often requires cultural understanding and moral commitment that go beyond algorithms. Similarly, caregivers for children, the elderly, or disabled perform not just physical tasks but provide companionship and emotional support. A robot caretaker cannot truly comfort an elderly person who feels lonely. Society will continue to need humans in these nurturing and altruistic roles. Median Salary: Childcare Workers ~$27,490; Personal Care Aides ~$29,430 – often low, reflecting undervaluation, yet these jobs are crucial. Outlook: Very high demand – Home health and personal care aides are the #1 fastest-growing occupation in the U.S. (estimated ~+25% by 2031) (Charts of the largest occupations in each area, May 2023), precisely because technology cannot replace the essential human touch they provide.
These “insulated” jobs share a common theme: they play to uniquely human strengths – creativity, empathy, dexterity, complex decision-making, and interpersonal connection. They are not “automation-proof” forever (few things are), but they are automation-resistant given current and foreseeable technology. In many of these fields, AI will serve as a tool to enhance human workers, not replace them. For example, teachers might use AI to personalize lesson plans, and doctors use AI to analyze medical scans – but in both cases, the human is still leading. As a pro tip, even people in these fields should stay tech-savvy: “AI-proof” jobs can still benefit from AI for efficiency (AI-proof Jobs: 22 Roles Least Likely to Be Replaced by Artificial Intelligence – Career Services | Empire State University), so adopting useful tech can make these workers even more effective, securing their roles in the future.
The impact of automation on jobs is not uniform around the world. Labor markets in different regions face distinct challenges and adoption rates of AI/robotics:
High-Wage Economies (U.S., Europe, East Asia): In countries like the United States, Germany, Japan, and South Korea, the cost of labor is high and businesses have strong incentives to automate. These nations are at the forefront of robotics adoption. For instance, South Korea and Japan have heavily automated manufacturing – South Korea leads the world with 1,012 industrial robots per 10,000 manufacturing workers, far above the global average (151) and the U.S. (285) (Which Countries Have the Most Industrial Robots?). Japan and Germany also have robot densities 3–4× the global average (Which Countries Have the Most Industrial Robots?). Aging populations in places like Japan and Western Europe add pressure to automate, as fewer working-age people are available for certain jobs. In these economies, industries like manufacturing have already shed many routine jobs to robots (e.g., automotive factories in Japan are famously lights-out). Now, AI is moving into service sectors (banking, retail, etc.). The pace of AI adoption is rapid – a majority of employers in developed countries plan to integrate AI in some form by 2030 (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog) (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). As a result, workers in rich countries may feel the displacement effects sooner, but these countries also have more resources to invest in new job creation (in tech, green energy, etc.) and retraining.
Emerging Economies with Cheaper Labor (e.g. Southeast Asia, South Asia, Africa): In regions where wages are low, the economics of automation are more complicated. Companies have historically offshored labor-intensive work (textile manufacturing, basic assembly, call centers) to lower-wage countries instead of automating. For example, a garment factory in Bangladesh or customer service center in the Philippines might still use hundreds of workers, because their wages are low enough that automation isn’t immediately cost-effective. This can delay the adoption of AI/robots in certain sectors of developing economies. For instance, Southeast Asian countries have a robot density below the global average, reflecting their reliance on labor-intensive industry. However, this delay is not indefinite – as AI and robots get cheaper and more capable, and as some developing countries’ wages rise, automation will start making inroads. An International Labour Organization study found approximately 56% of jobs in five ASEAN countries (Thailand, Vietnam, Philippines, Indonesia, Cambodia) are at high risk of automation in the next 10–20 years () (). Vietnam, for example, has a very high share of jobs that could be automated (up to 70% by some estimates) (), because many people work in manufacturing or agriculture doing routine tasks (). The difference is that, for now, those jobs are still being done by people due to lower labor costs and slower tech rollout. In short, emerging markets might experience a later wave of automation – potentially sudden if companies decide to “leapfrog” to automated processes instead of following the traditional path of gradual industrialization.
China: China deserves special mention – it has aspects of both. China is rapidly automating (robot installations in China now outpace every other country, and its robot density jumped to 392 per 10k workers (Which Countries Have the Most Industrial Robots?)). This is driven by rising wages and huge scale. Three of the world’s 10 largest employers are Chinese organizations, and they are automating fast. For example, Foxconn in China (electronics manufacturer) replaced tens of thousands of workers with robots in a single factory push (CLSA, WEF, and Citi on the Future of Robots and AI in the Workforce - Business Insider). However, China also still employs millions in labor-intensive sectors (textiles, basic electronics assembly) in inland regions. So within China, the coastal high-tech factories are highly automated, while other areas still rely on human labor – a microcosm of global disparities.
Effects on Low-Cost Labor Economies: A critical question is whether automation will undercut the advantage of cheap labor. If a robot in the U.S. can do the work at a similar or lower cost than a worker in Laos or Kenya, manufacturers might relocate production closer to home (a process known as “reshoring”) and simply use robots. This could reduce job opportunities in developing countries that previously benefited from offshoring. On the other hand, developing countries themselves can adopt automation to boost productivity. The impact will vary: countries with a skilled workforce and strong infrastructure might embrace advanced manufacturing (e.g. robot-powered factories in Malaysia), whereas least-developed countries might struggle to compete if they lose labor-cost advantages and cannot afford automation investment. There’s concern that automation could widen global inequality – with wealthier nations reaping productivity gains and poorer nations facing job losses without comparable new tech jobs to replace them. However, emerging economies also have growing domestic markets and other sectors (construction, services, healthcare) that will generate employment and are less automatable in the near term.
Regional Policy and Culture Differences: Attitudes and policies also shape adoption. Europe, for example, tends to have stronger worker protections and has been proactive in discussions of AI ethics and regulation. The EU is considering regulations on AI use in the workplace, which might slow deployment compared to the U.S. if companies must meet certain requirements. In Japan and South Korea, cultural comfort with robots (and necessity due to demographics) means automation is embraced – you’ll find robots in Japanese elder care homes or as hotel receptionists, something less common in other cultures. In contrast, countries with abundant young labor (India, much of Africa) have less immediate pressure to automate and may prioritize job creation for their populations over labor-saving automation in the short term.
In summary, developed countries are seeing faster workforce automation – replacing jobs that are high-paid (to save costs) or unpleasant (to improve efficiency), while developing regions thus far leverage their lower wages to keep humans in roles a bit longer. But the trend lines are converging: as AI/robotics become ubiquitous and cheaper, the impact on jobs will be global. Each region will need to manage the transition in line with its economic conditions – whether that means investing in tech education for new high-skill jobs, or creating social safety nets for displaced workers, or both.
It’s not all displacement – AI and robotics are also creating new jobs and industries. Historical technological shifts show that while some jobs vanish, others emerge. The rise of AI is already spurring demand for new kinds of work and expanding certain fields. Here are some of the careers and opportunities growing thanks to AI advancement:
Data Scientists and Big Data Specialists: The flood of data generated by digital systems and IoT devices has led to huge demand for those who can analyze and interpret data. AI thrives on data, so organizations need data scientists to collect, clean, and model data for AI projects. In fact, “Big data specialists” is ranked the #1 fastest-growing role in WEF’s Future of Jobs 2025 report (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). Skills/qualifications: Strong background in statistics, programming (Python/R), machine learning, and knowledge of database systems. Many have a Master’s or PhD in data science or related fields, but intensive bootcamps and certifications are also pathways.
AI/Machine Learning Engineers: These are the people who build and refine AI systems. As companies race to deploy AI, they need experts to develop algorithms, train models, and maintain AI infrastructure. Machine learning engineers design neural networks, fine-tune AI models (like recommendation engines or image recognition systems), and work on improving AI performance. This role is listed among the top emerging jobs (WEF ranks “AI and Machine Learning Specialists” #3 in growth) (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). Skills: Proficiency in programming (Python, C++), familiarity with ML frameworks (TensorFlow, PyTorch), mathematics (linear algebra, calculus, probability), and often an advanced degree in computer science or AI. Many also come via online courses and self-learning due to the field’s rapid evolution. Salary: AI engineers are well-paid – often six figures in the U.S. due to scarce talent.
Software Developers (Especially AI/Automation Software): Far from being obsoleted, software developers are in higher demand to create the next generation of applications – many of which have AI components. WEF ranks “Software and Applications Developers” as #4 fastest-growing job (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). Developers are needed to integrate AI into products, develop user interfaces for AI-driven services, and build the cloud systems that run AI algorithms. Additionally, Robotics engineers (a specialized software/hardware developer) are needed to design and program robots for manufacturing, healthcare, logistics, etc. Skills: Traditional computer science and software engineering skills (coding, system design), plus knowledge of AI APIs or robotics kinematics depending on the role. Outlook: The U.S. BLS projects software developer jobs to grow ~25% in the 2020s (The US Bureau of Labor Statistics predicts a 25% increase ... - Reddit), much faster than average, partly because of AI-related development.
DevOps and AI Ops Specialists: As AI becomes integrated in company workflows, there’s a need for professionals to manage the deployment and scaling of AI models. MLOps (Machine Learning Operations) engineers ensure that machine learning models move from the data science lab into production smoothly and continue working reliably. This is an emerging niche blending software engineering, data engineering, and DevOps. Skills include familiarity with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and continuous integration. These roles often require knowing how to monitor AI systems for bias or drift over time – a new challenge unique to AI applications.
Cybersecurity Analysts and Security Specialists: With AI adoption comes new security concerns – AI systems themselves need protection (from tampering or adversarial attacks), and AI is used to both defend and attack systems. Cybersecurity jobs are booming as companies prioritize protecting data and AI models. Automated attacks are growing, but so are AI-driven defense tools (intrusion detection using ML, etc.). Skills: Networking, encryption, threat analysis, plus knowledge of AI-driven security tools. WEF lists “Security Analysts” among growing roles as well (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). The upside is that cybersecurity is relatively automation-resistant (attackers and defenders are in a cat-and-mouse game, often requiring human creativity), so it’s a good field to enter.
FinTech Engineers and Analysts: AI is transforming finance (algorithmic trading, risk modeling, fraud detection), giving rise to FinTech (financial technology) roles. WEF ranks “FinTech Engineers” as #2 fastest-growing job (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). These are experts who develop and manage AI-driven financial services – for example, an engineer who creates a robo-advisor platform for investments, or a credit analyst who uses AI to improve credit scoring models. Skills: Combination of finance domain knowledge and data science/AI skills. Often a degree in finance or computer science (or both), or specialized FinTech certifications.
Autonomous Vehicle Specialists and Drone Operators: As autonomous cars, trucks, and drones roll out, a new ecosystem of jobs is emerging. Autonomous vehicle (AV) technicians and specialists are needed to develop and maintain self-driving car systems – WEF lists “Autonomous and Electric Vehicle Specialists” in top emerging roles (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). These might include sensor calibration experts, AV safety drivers/engineers who supervise tests, and fleet technicians who service autonomous vehicle fleets. Similarly, drones used for delivery or surveying require operators, maintenance technicians, and regulatory compliance specialists. Skills: For AV – robotics, computer vision, automotive engineering. For drones – pilot certification, knowledge of airspace rules, and tech skills to operate and repair UAVs.
AI Ethics and Policy Experts: The rise of AI has brought ethical questions (bias, privacy, AI decision transparency). We see new roles like AI ethicist, AI policy advisor, AI compliance officer emerging within organizations to ensure AI is used responsibly and meets regulatory requirements. Governments and NGOs are also hiring experts to craft AI regulations and guidelines. People in these roles often have a background in ethics/philosophy or law, plus understanding of AI technology. This field is nascent but growing as the societal impacts of AI draw attention.
“Prompt Engineers” and AI Trainers: A very new category born from generative AI’s rise is the “prompt engineer” – someone who specializes in writing and refining prompts to get desired outputs from AI models like ChatGPT. While it might not remain a long-term standalone job (if AI tools get better at understanding intent), in the short term companies are hiring experts who know how to coax the best results from AI for tasks like copywriting, coding assistance, or image generation. Likewise, AI systems need continuous training: AI trainers or data annotators label data and correct AI outputs to improve accuracy (for example, rating the quality of a search engine result or training an AI to better recognize edge cases). These roles didn’t exist in the same way a decade ago. They often require moderate tech savvy and domain-specific knowledge; prompt engineering requires creativity with language and understanding the AI’s workings.
Healthcare Technologists (Telemedicine, AI Diagnostics): Rather than replacing doctors, AI is creating new support roles. For instance, telemedicine coordinators and digital health specialists manage AI-assisted healthcare delivery. Radiology technologists now work with AI that pre-scans images – someone needs to validate and feed those AI systems. Genetic counselors and bioinformaticians interpret AI-driven genetic analyses for patients. All these are growth areas as medicine integrates big data and AI.
Robotics Technicians and Maintenance: Every new robot deployed in a factory or warehouse needs installation, maintenance, and repair. Thus, robotics technician is a growing occupation. These technicians set up robotic equipment, perform routine maintenance, and troubleshoot issues (sensors going out of calibration, etc.). It’s a skilled trade that combines mechanical, electrical, and programming knowledge. Outlook: As the use of robots expands in manufacturing and logistics, demand for people to service them goes up. These jobs often require an associate’s degree or technical certification. The salary is solid (often $50k–$70k range) and the work is hands-on – a new-age “blue collar” job created by automation itself.
Green Energy and Sustainability Roles (boosted by AI): Interestingly, the green economy is benefiting from AI, and it’s creating jobs. Renewable energy engineers (solar, wind) use AI to optimize grids and storage, making those roles more crucial – WEF lists “Renewable Energy Engineers” among top growth jobs (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). Environmental engineers and urban planners use AI to model climate impacts. So as AI helps address climate change, jobs in sustainability are expanding rather than shrinking. Many of these roles are engineering or science-based but now require familiarity with AI tools for data analysis or optimization.
In essence, industries growing due to AI include tech of course (AI development itself), but also any industry undergoing digital transformation. Software, IT services, finance, advanced manufacturing, healthcare, education tech, and green tech are all seeing growth in roles that require a blend of domain expertise and AI literacy. For example, education companies hire learning experience designers to create AI-driven tutoring systems; agriculture companies hire precision agriculture specialists to use AI drones for crop management. Rather than AI being a job-killer only, it’s also an innovation driver spawning whole new career paths – many of which were unheard of even 5–10 years ago.
In-demand skills for these new roles often combine technical know-how in AI (like machine learning, programming, statistics) with traditional skills of the domain (like finance basics for FinTech, or drawing skills for a designer working with AI tools). Additionally, soft skills remain key: problem-solving, critical thinking, and adaptability. According to the World Economic Forum, analytical thinking and AI/Big Data skills top the list of growing skills, but they are closely followed by creative thinking and resilience – showing that human creativity and adaptability are still very much required (The Future of Jobs Report 2025 | World Economic Forum) (The Future of Jobs Report 2025 | World Economic Forum). Many workers are upskilling via online courses in data science, AI, and cloud computing to transition into these emerging careers.
As AI and robotics reshape the job landscape, workers, industries, and governments must adapt. Here are some key insights on how the workforce can stay ahead of AI-driven changes:
Lifelong Learning – Focus on Skills that Complement AI: To remain employable, individuals should cultivate skills that AI finds difficult. These include creative thinking, complex problem-solving, interpersonal communication, and emotional intelligence (The Future of Jobs Report 2025 | World Economic Forum). For example, a customer service professional should develop expertise in handling escalated issues and emotional customers – tasks a bot might hand off to a human. STEM skills are also crucial; even basic coding or data literacy can be valuable in many jobs as workplaces integrate AI tools. The fastest-growing skills, according to WEF, include not just AI and Big Data knowledge, but also leadership, social influence, resilience, flexibility, and agility (The Future of Jobs Report 2025 | World Economic Forum) (The Future of Jobs Report 2025 | World Economic Forum). This suggests a blend of technical and “human” skills is the recipe. Many experts advise workers to “partner with AI” – learn to use AI tools to augment your productivity. For instance, marketers are learning to use AI analytics for customer insights, and architects use AI-driven simulation software – those who embrace these tools can focus on higher-level work and outpace those who don’t. Essentially, continuous upskilling is the new normal; workers should be ready to periodically refresh their skillsets as technology evolves.
Fastest-Growing AI-Proof Industries: While no industry is entirely immune to change, some sectors are inherently more “human-centric” or poised for growth in the AI era:
Healthcare and Elder Care: With aging populations worldwide, healthcare jobs (nurses, therapists, home health aides) are booming and relatively safe from full automation. These roles require human empathy and physical presence. The care economy in general (elder care, childcare, personal services) is expected to add millions of jobs (The Future of Jobs Report 2025 | World Economic Forum) (The Future of Jobs Report 2025 | World Economic Forum).
Technology and AI Development: It might seem paradoxical, but the more AI proliferates, the more jobs for people to develop, manage, and improve AI. The tech sector will continue to see high growth – AI research scientists, software developers, IT project managers, and so on. Jobs in computing and mathematics are projected to grow as they form the backbone of the AI-powered world.
Green Energy and Infrastructure: Industries like renewable energy, electric vehicles, and smart infrastructure are expanding (often with help from AI for efficiency). Governments and businesses are investing heavily in these areas, creating robust job demand from wind turbine technicians to electrical engineers and urban planners. These fields involve a lot of physical building and engineering judgment – hard to automate fully – and are priorities globally (many new jobs are being created through climate initiatives).
Creative Economy and Experience Economy: In an AI-saturated world, human creativity and experiences may become more valued. Think of live entertainment, gaming, arts, tourism, culinary arts – people will seek unique human experiences. We already see a booming market for experiential dining, live concerts, and video game design (where creative designers and story writers are crucial). AI can assist in these industries (like special effects in movies), but the creative drivers remain human.
Education and Training: As the need for reskilling grows, education is a growth industry. This includes not only traditional schools but also corporate training, online education platforms, and edtech. Curriculum designers, corporate trainers, and coaches who can help workers upskill in new technologies (including AI) are in demand. Interestingly, education is doubly insulated: it’s needed to cope with AI changes, and it’s hard to automate the teaching process entirely (as discussed, teachers remain vital).
Adaptation Strategies for Workers: Embrace a mindset that your career will evolve. Practical steps include pursuing certifications in high-demand areas (data analytics, cloud computing, project management), seeking interdisciplinary knowledge (e.g. if you’re in marketing, learn some data science; if you’re in finance, learn Python for financial analysis), and honing soft skills. Networking and personal branding are also important – humans will still hire other humans, so demonstrating your unique value (creative portfolio, leadership experience, etc.) will help you stand out beyond what’s on a resume that AI might also have. Another strategy is to move into roles that use AI rather than compete with it – for example, radiologists are adopting AI tools to become more efficient rather than fearing them, using the time saved to consult more with patients or focus on complex cases.
Support for Workers: Retraining and Transition Programs: Companies and governments recognize the need to help workers transition. Many large employers are investing in reskilling programs for their staff – for instance, Amazon’s Upskilling 2025 initiative invests in training employees for higher-skilled roles in IT, healthcare, etc., knowing that warehouse and call center jobs may decline. Governments are also responding: countries are considering policies like “lifelong learning accounts” (personal education budgets workers can use to retrain), or expanding vocational training in tech. The World Economic Forum emphasizes that up to 50% of workers will need reskilling by 2025 due to automation (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). Encouragingly, about 85% of employers in one survey said they plan to upskill or reskill their workforce to meet changing skill needs (WEF Future of Jobs Report 2025 reveals a net increase of 78 million jobs by 2030 and unprecedented demand for technology and GenAI skills - Coursera Blog). This suggests many companies prefer to transform their workforce rather than simply cut jobs – turning, say, a displaced data entry clerk into a data analyst through training.
Government Policies and Regulations: Policymakers are actively discussing how to manage AI-driven job displacement. A variety of ideas are on the table:
Education reforms: Emphasizing STEM, coding, and critical thinking from early education onwards, so the future workforce is AI-ready. Also, making retraining easier – for example, community colleges updating curricula to include AI and robotics maintenance, or offering free/subsidized tech bootcamps for mid-career workers.
Labor Market Policies: Some propose a form of “Automation Adjustment Assistance”, akin to trade adjustment assistance. For instance, the Urban Institute suggests expanded benefits and retraining support for workers laid off due to AI (How Government Can Embrace AI and Workers | Urban Institute). This could include wage insurance (to cushion pay cuts when switching fields) or relocation assistance if new jobs are in different regions.
Reduced Work Hours and Job Sharing: As productivity rises with AI, some argue we could shift to shorter workweeks to distribute work. Trials of four-day workweeks in some countries tie into this – if AI lets us produce the same output in less time, humans could work less (this requires societal and business buy-in, of course).
Universal Basic Income (UBI) or Social Safety Nets: The idea of a UBI – a guaranteed income floor for all citizens – gained traction as a possible solution if massive job loss occurs. It was debated in the context of automation by tech leaders. While no major economy has implemented full UBI yet, pilots have been run (e.g., in Finland, and some U.S. cities). Alternatively, strengthening unemployment benefits, healthcare, and pensions can ensure those who lose jobs to AI aren’t left destitute.
“Robot Tax” and Incentives: To slow down displacement, some have floated a tax on companies that replace human workers with robots – the tax revenue could fund retraining programs for displaced workers. This was notably suggested by Bill Gates. No country has a robot tax yet, but it reflects the policy brainstorming happening. On the flip side, governments also provide incentives for job creation in growing sectors (like subsidies for hiring in green energy or care jobs to offset losses elsewhere).
AI Regulation in Hiring/Firing: Lawmakers are looking at rules to ensure AI doesn’t unfairly eliminate or penalize workers. For example, some jurisdictions require notice if AI is used to evaluate employees or job applicants. The EU’s draft AI Act would regulate “high-risk” AI uses, potentially including HR algorithms. Some U.S. states (e.g., Illinois) have laws about AI in video interviews to protect candidates. These regulations aim to prevent hidden biases in AI from causing unjust job loss or blocked hiring.
Public-Private Collaboration: Dealing with AI-driven workforce changes often involves partnerships. Tech companies, educational institutions, and government agencies are partnering to deliver training at scale. For instance, Microsoft and LinkedIn have offered free AI and digital skill courses to millions globally, often in collaboration with governments. The World Economic Forum’s Reskilling Initiative encourages businesses to pledge retraining for workers. Community colleges and employers are collaborating on apprenticeships in fields like cybersecurity and robotics, which create new career on-ramps for displaced workers. These joint efforts are crucial, as no single entity can solve the transition alone.
In conclusion, adapting to AI and robotics is a multifaceted challenge. Workers should focus on being flexible, tech-savvy, and people-savvy, continually updating their skills. Industries should innovate in job design, using humans for what they do best and machines for the rest. Governments should provide frameworks and safety nets so the transition is smooth and inclusive. History shows technology creates new prosperity in the long run, but the path can be bumpy – with smart planning and an emphasis on human-centric skills, the workforce can navigate the AI revolution and even thrive alongside it.
Sources: World Economic Forum – Future of Jobs 2025 report (The Future of Jobs Report 2025 | World Economic Forum) (The Future of Jobs Report 2025 | World Economic Forum); McKinsey Global Institute – various workforce analyses; U.S. Bureau of Labor Statistics – Occupational Outlook; International Federation of Robotics – automation statistics (Which Countries Have the Most Industrial Robots?).