Will AI create or take away more job opportunities?

Short answer: Most major forecasts say AI will create slightly more jobs than it destroys overall — but the transition will be uneven, disruptive, and painful for specific groups of workers.

The big-picture numbers

The most widely cited forecast, the World Economic Forum's Future of Jobs Report 2025, surveyed over 1,000 leading global employers representing more than 14 million workers across 22 industry clusters and 55 economies. It found that by 2030, 92 million jobs will be displaced, and 170 million new ones will be created, a net increase of 78 million.

However, it's important to note this isn't an AI-only figure — it's a net gain that covers every force reshaping work, not AI alone, and also bakes in the green transition, demographic shifts, geoeconomic fragmentation, and economic conditions.

McKinsey Global Institute's 2025 US-focused analysis reaches a similar directional conclusion: AI-driven automation reduces demand by 32 million workers, but human economy evolution, physical economy revival, tech acceleration, and new AI-era occupations more than offset that drag—41 million added against 36 million lost, for a net gain of jobs. A related Fortune summary of this research put it more simply: AI and automation will cut demand for about 36 million U.S. jobs by 2035 while growth elsewhere creates about 41 million.

But the "net positive" headline hides real pain

1. The transition isn't smooth for individuals. Even in McKinsey's optimistic scenario, only one in seven displaced workers has a direct path into a growing job that needs little retraining and pays at least as much, while nearly half face an "unpaved" path blocked by large skill gaps or credential requirements, and about 85% of growing jobs require a credential.

2. Skills gaps are the biggest barrier. The WEF found employers expect 39% of key skills required in the job market will change by 2030, though this is down from 44% in 2023. Overall, the skills gap continues to be the most significant obstacle to business transformation, cited by 63% of employers, and if the global workforce were represented by 100 people, 59 would need reskilling by 2030 — 11 of whom are unlikely to receive it, translating to over 120 million workers at medium-term risk of redundancy.

3. Forecasts vary widely depending on methodology. Estimates range considerably:

4. Entry-level workers appear most vulnerable. In 2025, the labour market faced growing concerns at the entry-level, with opportunities shrinking just as workforce participation from younger generations peaked — entry-level job postings have fallen by 29% since January 2024. One stark example: in the UK, 1.2 million graduates competed for just under 17,000 entry-level positions in 2024.

5. New kinds of jobs are emerging that don't look like "AI jobs." Interestingly, much of the visible job creation isn't in AI labs but in supporting infrastructure — in cities like Columbus, Ohio and Reno, Nevada, big tech hiring jumped from under 2% of local postings to more than 10% between mid-2025 and mid-2026, with the clearest job creation showing up in switchgear, cooling loops and electrical panels rather than programming roles.

6. Which jobs are projected to grow vs. decline:
Growth is expected to be concentrated in frontline and care roles: Frontline job roles are predicted to see the largest growth in absolute terms, including Farmworkers, Delivery Drivers, Construction Workers, Salespersons, and Food Processing Workers, while Care economy jobs such as Nursing Professionals, Social Work and Counselling Professionals, and Personal Care Aides are also expected to grow significantly. Meanwhile, McKinsey finds the largest declines are expected in retail trade and in accommodation and food services, which together could account for most sector-level job losses.

Bottom line

On net, most authoritative forecasts (WEF, McKinsey, Goldman Sachs) lean toward AI being a net job creator globally when you factor in broader economic growth and new industries — but the margin is thinner than headlines suggest, the churn is massive (roughly a fifth of all jobs affected), and the benefits and costs land very unevenly. Entry-level workers, those in routine white-collar roles (data entry, certain administrative/customer service work), and workers without easy access to retraining are likely to bear the brunt of displacement, while demand surges for AI-fluency skills, infrastructure/trades work, healthcare, and "human-centric" roles that are harder to automate.