Useful Info: List of jobs that will get worse, better and stay the same roughly, due to AI

Seth Walsh

Seth Walsh

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  • GETS MUCH WORSE — the real danger zone
    • Data-entry clerks — catastrophic bargain. Essentially pure machine-readable transformation.
    • Administrative assistants / generic secretaries — scheduling, documents, correspondence, expense processing, coordination increasingly automated.
    • Basic executive assistants — same. Exception: genuinely trusted chief-of-staff-style EAs.
    • Bookkeepers — very bad.
    • Accounts payable / receivable clerks — very bad.
    • Payroll processors — bad.
    • Basic tax preparers — bad.
    • Junior audit grunt work — sampling, testing, documentation, drafting workpapers gets heavily compressed.
    • Insurance claims processors — bad.
    • Loan-processing staff / mortgage administrators — bad.
    • Generic bank operations — settlements, reconciliations, static-data work, exception processing.
    • Fund administration / NAV production — progressively worse.
    • Transfer agency — progressively worse.
    • Routine middle-office finance — worse.
    • Trade reconciliation / matching roles — worse.
    • Routine reference-data operations — worse.
    • Manual KYC/AML screening — worse, although senior investigation remains valuable.
    • Routine compliance monitoring — worse.
    • Customer-service agents / call centres — one of the clearest losers.
    • Tier-1 IT helpdesk — bad.
    • Basic technical support — bad.
    • Transcription — essentially destroyed.
    • Translation of ordinary commercial material — severe commoditisation.
    • Proofreading / basic editing — bad.
    • Commodity copywriting — brutal.
    • SEO content writing — brutal.
    • Generic social-media content production — bad.
    • Low-end graphic design — bad. WEF now places graphic designers near its fastest-declining group, a major reversal from 2023. World Economic Forum
    • Stock photography / basic commercial illustration — bad.
    • Basic video editing — deteriorating quickly.
    • Voiceover work / commodity narration — bad.
    • Legal secretaries — bad.
    • Document-review lawyers — very bad.
    • Basic paralegal research — bad.
    • Junior legal drafting — substantially compressed.
    • Routine contract drafting — worse.
    • Junior consulting analyst grunt work — slide creation, desk research, benchmarking, summarising interviews, Excel analysis.
    • Market-research assistants — worse.
    • Basic corporate research analysts — worse.
    • Junior equity-research production work — model updates, transcript summaries, industry scraping, first-pass writing.
    • Generic junior financial analysts — worse. ILO's latest work specifically finds rising exposure among financial analysts and investment advisers. International Labour Organization
    • Investment-banking analyst production work — fewer humans can create vastly more material. The elite seats remain valuable; the apprenticeship pyramid gets thinner.
    • FP&A analysts doing reporting rather than decision-making — worse.
    • Basic business analysts — worse.
    • PMO coordinators — bad.
    • Project coordinators whose job is meetings, minutes, status updates and chasing people — very bad.
    • Generic recruiters / CV screeners / sourcing coordinators — worse.
    • HR administrators — worse.
    • Routine procurement analysts — worse.
    • Commodity sales-development reps doing outbound email — bad.
    • Basic travel agents — worse.
    • Cashiers / ticket clerks — continued deterioration; explicitly among WEF's fastest-declining roles. World Economic Forum
    • Printing/prepress occupations — continued structural decline.
    • Routine warehouse workers — robotics rather than LLMs is the threat.
    • Basic factory assembly — robotics increasingly compresses labour.
    • Junior “CRUD” programmers — bad relative to the extraordinary deal software juniors got in 2010–2021.
    • Basic web developers — worse.
    • WordPress/template-site production — extremely commoditised.
    • Manual QA testers — worse.
    • Junior application programmers doing well-specified implementation — worse. ILO specifically records increasing GenAI exposure for application programmers and web developers. International Labour Organization
    • People whose job is fundamentally “receive digital information → manipulate it according to rules → send digital information somewhere else.” This is the master category.
  • GETS WORSE, BUT THE OCCUPATION REMAINS IMPORTANT
    • Accountants — fewer people can produce much more accounting output. Senior advisory/accountability gets stronger; production accounting weaker. WEF actually places accountants and auditors among declining occupations. World Economic Forum
    • Lawyers overall — law survives. The junior pyramid gets squeezed. Partners with clients, reputation and judgement become more leveraged.
    • Software engineers overall — demand can continue growing while the average coding task becomes cheaper. WEF still places software/application development among fast-growing roles. World Economic Forum The split becomes enormous between “person who writes code” and “person who can own a system/product.”
    • Financial analysts — fewer analysts required per dollar of assets/revenue; good analysts acquire vastly more capability.
    • Management consultants — prestige firms survive, but information-production leverage changes enormously.
    • Corporate finance — less spreadsheet labour, more interpretation/business partnering.
    • Marketing — execution gets cheap; distribution, brand, taste and ownership matter more.
    • Journalism — commodity news production gets uglier; genuinely sourced reporting remains scarce.
    • University academics — teaching material becomes abundant; elite research, reputation and original intellectual contribution remain valuable.
    • Architects — drafting/rendering gets commoditised; approvals, client judgement, design accountability remain.
    • Junior engineers — routine calculation/documentation gets automated while licensed engineering judgement remains.
    • Radiologists/pathologists — enormous AI augmentation, but medicine's liability, integration and clinical judgement make complete commoditisation much harder than people once assumed.
    • Pharmacists — dispensing increasingly automated; clinical interaction remains.
    • Real-estate agents — information advantage collapses further; rainmaking, negotiation and local networks survive.
    • Generic corporate managers — worse if their function is information aggregation and coordination.
    • Middle management generally — vulnerable. AI lets one strong manager oversee more information and more people.
    • Government administrative employees — unusually protected from firing, but not from automation, hiring freezes or long-term skill devaluation.
    • Teaching — AI makes lesson creation/tutoring dramatically easier, but demographic/social demand remains. WEF expects large absolute growth in education jobs. World Economic Forum
    • Truck/delivery driving — probably okay near term; autonomous driving creates a longer-term ceiling.
    • Taxi/private-hire driving — same basic issue.
    • Warehouse/logistics supervision — survives but increasingly manages automated systems rather than labour.
  • ROUGHLY THE SAME / RELATIVELY DEFENSIVE
    • Hairdressers/barbers
    • Beauty therapists
    • Chefs
    • Bartenders
    • High-end hospitality
    • Plumbers
    • Electricians
    • Carpenters
    • HVAC technicians
    • Mechanics
    • Auto electricians
    • Roofers
    • Welders
    • Construction trades
    • Equipment technicians
    • Field-service engineers
    • Aircraft-maintenance technicians
    • Dentists
    • Dental hygienists
    • Physiotherapists
    • Occupational therapists
    • Paramedics
    • Police
    • Firefighters
    • Pilots
    • Air-traffic controllers
    • Childcare workers
    • Care assistants
    • Hospitality/service workers where presence itself is the product
      These aren't necessarily spectacular careers. They're simply protected by physical reality, locality, licensing, trust or human presence. A plumber doesn't suddenly become ten plumbers because GPT gets better.
  • GETS BETTER
    • AI/ML engineers — obvious.
    • AI research scientists — obvious.
    • AI infrastructure engineers — compute, inference, distributed systems, deployment.
    • Data engineers working on real production systems
    • Cybersecurity engineers
    • Information-security specialists — WEF has information security among its fastest-growing occupations. World Economic Forum
    • Security-management specialists
    • Robotics engineers
    • Controls/automation engineers
    • Semiconductor engineers
    • Power/grid engineers
    • Data-centre engineering and operations
    • Renewable-energy engineers
    • Electrical engineers tied to electrification/infrastructure
    • Nuclear engineers / technically scarce energy roles
    • Highly capable systems engineers
    • Senior software engineers who own architecture rather than tickets
    • Product engineers capable of going problem → product almost alone
    • Technical founders
    • Entrepreneurs generally — cost of creating a company drops enormously.
    • Small-business owners capable of automating administration
    • Owner-operators in skilled trades — particularly strong combination: physical scarcity + AI handling office work.
    • Complex enterprise salespeople — AI gives one salesperson vastly better research/preparation, while trust and closing remain human.
    • Relationship-driven institutional sales
    • Rainmakers
    • Senior recruiters with genuinely valuable networks rather than CV processing.
    • Dealmakers
    • M&A originators
    • Private-equity professionals with actual investment authority
    • Venture investors with genuine sourcing/selection ability
    • Portfolio managers
    • Traders with genuine P&L ownership
    • Quant researchers
    • Quant traders
    • Electronic-trading engineers
    • Market-making technologists
    • Risk takers whose edge comes from judgement/model design rather than report generation
    • Senior investment professionals responsible for capital allocation
    • CFOs/finance leaders making decisions rather than producing reports.
    • COOs who actually redesign systems
    • Strong general managers with P&L responsibility
    • Senior product managers with genuine product judgement
    • Operations people who can automate entire operating systems, rather than merely operate them.
    • Doctors, particularly highly skilled specialists.
    • Surgeons
    • Anaesthetists
    • Specialist nurses / nurse practitioners
    • Nurses generally — ageing populations make demand exceptionally persistent; WEF predicts substantial growth. World Economic Forum
    • Mental-health clinicians / counsellors where therapeutic relationship matters.
    • Scientists capable of combining AI with real experimental work
    • Biotech researchers
    • Drug-discovery researchers
    • Materials scientists
    • Elite academics doing genuinely novel research
    • Energy/infrastructure developers
    • Construction project leaders capable of managing real-world execution
    • High-end technical consultants with accountability for outcomes
    • Anyone with regulatory sign-off / personal professional liability where AI does the analysis but a scarce human must make the decision
    • Anyone controlling distribution
    • Anyone controlling customers
    • Anyone controlling capital
    • Anyone controlling valuable proprietary data
    • Anyone controlling intellectual property
    • Anyone whose compensation is directly attached to revenue or P&L
    • Owners of productive assets.
 
  • +1
Reactions: ruikundumb, mendeds, pexy and 4 others
Wow, great thread. You obviously put in msny hours into this, thanks a lot
 
  • JFL
Reactions: Navity
Wow, great thread. You obviously put in msny hours into this, thanks a lot
1791321276535

:p
 
  • Love it
Reactions: WBC323
Wow, great thread. You obviously put in msny hours into this, thanks a lot
he put probably like 1-2 minutes of effort in to the thread lmao
here's what he likely did:
- "chatgpt, give me a list of jobs and list how they will change from AI"
- copy and paste
 
what about diplomacy/development
 

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