Will AI Replace My Job?

How to read these results

This tool is based on automation research from the BLS, McKinsey Global Institute, Goldman Sachs, Oxford Economics, and the World Economic Forum. Risk levels reflect the current and near-term (5–10 year) outlook — not science fiction.

"High risk" doesn't mean your job disappears next year. It means a significant portion of the tasks in that role can already be done by AI systems, and that trend is accelerating. "Low risk" means the core of the work requires human presence, judgment, relationships, or physical dexterity that AI cannot replicate today.

For a tech-sector deep dive, see AI replacing developers: what's actually happening. For the entry-level picture across all industries, see AI replacing entry-level jobs.

AI job replacement timeline: 2026–2030

The most specific near-term forecasts cluster around 2026–2028 as the period when AI displaces a significant share of routine white-collar work — not science-fiction AGI, but the automation of tasks that currently fill 40–60% of the average knowledge worker's day.

• Anthropic CEO Dario Amodei (2025): AI could eliminate up to 50% of entry-level white-collar jobs within 1–5 years, naming coding, data analysis, and customer support as first.
• OpenAI CEO Sam Altman (2025): AI agents will begin doing the work of full-time employees "within the next few years," starting in software engineering.
• WEF Future of Jobs 2025: 40% of companies plan to reduce headcount in automatable roles. Net: +170M jobs created, −92M eliminated, by 2030.
• Goldman Sachs (updated 2025): Generative AI could automate the equivalent of 300 million full-time jobs globally — through partial automation, not elimination.
• Metaculus aggregate (2026): 25% probability of transformative AI (majority of economically valuable tasks) by 2028; 50% probability by 2032.

The pattern across forecasts: 2026 is when AI finishes eating the low-hanging fruit — routine document work, basic coding, first-tier support. 2027–2030 is when AI agents begin displacing roles that require coordination and judgment.

What happens when AI replaces all jobs?

Full job replacement is not a near-term scenario — but partial, sector-by-sector displacement is already underway, and the consequences are unevenly distributed.

The "who buys the products?" concern echoes historical worries about automation. The Industrial Revolution eliminated agricultural jobs and created factory jobs. Computers eliminated typing pools and created software engineering. Historically, cheaper production leads to lower prices, higher demand, and new industries. The question is whether AI is different in speed, scope, or distributional impact.

Why this wave may be different:

• Speed: Prior waves took decades. AI is compressing that into years. Workers displaced by factory automation in 1980 had 20 years to retrain. Workers displaced in 2026 may have 2.
• Cognitive work is the target: Every previous wave attacked physical or routine work. AI is the first to attack cognitive work — previously considered automation-proof. The retraining path is unclear.
• Concentration of gains: Productivity gains flow primarily to companies owning AI systems, not the workers they replace. Without policy intervention, this accelerates inequality.

Policy responses under debate: Universal Basic Income (UBI) pilots in Finland, Stockton CA, and Kenya show mixed results — participants work more, not less, but scale-up cost is enormous. The EU is studying a "robot tax" levied on AI-generated productivity to fund worker transition programs. No country has implemented one at scale.

The transition period — not the endpoint — is where the damage concentrates. Workers who lose jobs during the gap between AI displacement and new-job creation bear the cost. Track those developments at the daily AI briefing and the AI layoffs tracker.