AI’s Impact: Jobs at Risk and Safe Professions

- A Microsoft study identifies 40 professions likely to be automated by AI and 40 less vulnerable roles.
- This analysis, based on ChatGPT/Copilot interactions, sheds light on the evolving job market.
- It suggests AI will largely affect text- and communication-heavy roles, while hands-on professions remain safer.
Professions Facing Automation
Microsoft’s research, which analyzed over 200,000 interactions with AI systems like ChatGPT/Copilot, pinpoints professions highly susceptible to automation. These roles often involve text processing, oral communication, and summarizing extensive information, areas where AI currently excels. Translators, customer support specialists, authors, journalists, and data scientists are among the 40 professions identified as potentially being largely or entirely performed by artificial intelligence in the near future.
The list also includes roles such as telemarketers, statisticians, web developers, and management analysts, highlighting a broad impact across various sectors. Furthermore, professions like political scientists, historians, and advertising agents are also deemed vulnerable. This suggests that occupations relying heavily on information analysis and synthesis face significant transformation.
40 professions that may disappear due to AI
- Translators and interpreters
- Historians
- Flight attendants and tourist guides
- Sales representatives in the service sector
- Authors and writers
- Customer support workers
- CNC machine programmers
- Telephone operators
- Ticket collectors, railway/airline workers
- Radio presenters and announcers
- Brokerage clerks
- Home economics and farming courses
- Telemarketers
- Concierges
- Political scientists/political analysts
- News analysts, journalists, reporters
- Mathematicians
- Technical writers
- Proofreaders and text layout designers
- Support staff
- Editors
- Teachers of business disciplines at universities
- PR specialists
- Product demonstrators and promoters
- Advertising agents
- New account managers
- Statistical assistants
- Rental and hire managers
- Data Scientists
- Personal financial advisors
- Archivists
- University level economic teachers
- Web developers
- Management analysts
- Geographers
- Modellers
- Market analysts
- Employees of emergency services (operators)
- Switchboard operators
- Teachers of library science at the university level
Professions Less Vulnerable to AI
Conversely, the study identifies 40 professions considered least susceptible to AI automation. These roles typically demand physical dexterity, involve unpredictable situations, or necessitate complex interpersonal interactions that current AI systems cannot replicate. Examples include excavators, bridge builders, nurses, and roofers. Occupations such as massage therapists, surgeons’ assistants, and various medical support roles also fall into this category.
Additionally, jobs like divers, embalmers, and hazardous waste disposal workers require specific physical engagement in environments difficult for robots to navigate. This group emphasizes the enduring value of human capabilities in manual labor, healthcare, and situations requiring adaptive problem-solving.
Implications for the Workforce
The study underscores a clear trend: AI poses a greater challenge to office, creative, and administrative roles, but a lesser one to professions requiring physical work or direct healthcare. Microsoft emphasizes that AI’s primary purpose is to support human endeavors, not to completely replace them. However, the report cautions that individuals who do not adapt to modern AI tools risk being displaced. While AI’s influence on programming is significant, industry leaders believe a complete displacement of human programmers is not imminent, as complex tasks still benefit from human expertise.
40 professions considered to be the least vulnerable to AI
- Excavators
- Bridge and overpass builders
- Employees of water purification systems of water supply
- Manufacturers of casting moulds
- Layers of railway tracks and equipment
- Operators of pole setters
- Grinders and surface finishers
- Nurses and nursing assistants
- Motor boat captains
- Operators of logging equipment
- Workers in paving, coating and tamping
- Cleaners and housekeepers
- Workers at oil/gas facilities
- Roofers
- Compressor station operators
- Roofers’ assistants
- Tyre fitters
- Surgeon’s assistants
- Massage therapists
- Ophthalmologists and their assistants
- Operators of industrial tractors and trucks
- Chiefs of firefighters’ guards
- Workers with cement and concrete
- Dishwashers
- Agronomists
- Packers and operators of packaging machines
- Medical assistants
- Road workers
- Production assistants
- Periodontists and dental hygienists
- Repairmen
- Marine workers and engineers
- Car glass installers
- Oral and maxillofacial surgeons
- Farmers and farm equipment operators
- Divers
- Embalmers
- Painters and plasterers
- Hazardous waste disposal workers
- Vascular surgeons
The findings suggest that employees in high-risk areas should cultivate skills in interacting with AI. Mastering tools like Copilot, formulating effective prompts, and efficiently utilizing AI-generated data will be crucial. The labor market rules have undeniably shifted, making it essential to embrace AI rather than resist it. Leveraging AI’s power can accelerate work, reduce costs, facilitate more complex projects, and enhance the management of automated processes.
Broader Context: The Evolution of Human-AI Collaboration
It’s worth noting that the discussions around AI’s impact on employment often overlook the emergence of entirely new job categories that arise from technological advancements. Historically, new technologies have always reshaped the job market, creating roles that were previously unimaginable.
For instance, the rise of AI is already fostering demand for AI trainers, prompt engineers, and AI ethicists—roles centered on guiding, refining, and overseeing AI systems. This ongoing evolution suggests that while some jobs may disappear, others will emerge, transforming the nature of work rather than simply reducing it. The focus shifts from merely performing tasks to managing and collaborating with intelligent machines.