Will AI create or take away more job opportunities?

AI's net impact on jobs is hotly debated — I'll pull the latest research on whether it will create or cut more work.

On balance, most major forecasts project AI will create more jobs than it destroys in aggregate - but it will also destroy tens of millions of existing jobs, and the transition will be painful and uneven.

1. The headline projections: net creation

The most cited global projection is the World Economic Forum's Future of Jobs Report 2025:

> while 92 million jobs might be eliminated by 2030, 170 million new roles will be created because of AI, resulting in a net gain of 78 million

More detail from the same report:

> - The World Economic Forum projects 170 million new roles set to be created and 92 million displaced by 2030, resulting in a net increase of 78 million jobs, with job disruption equating to 22% of jobs by 2030

This is echoed elsewhere:

> - AI and data processing are expected to create 11 million new roles by 2030, while displacing 9 million - a net gain of 2 million jobs in that category alone, according to the World Economic Forum's Future of Jobs Report 2025
> - Overall, 170 million new jobs are projected to be created and 92 million displaced by 2030, resulting in a net increase of 78 million jobs globally (WEF Future of Jobs Report 2025)

McKinsey Global Institute makes a similar U.S.-specific forecast for a longer horizon:

> AI and automation will cut demand for about 36 million U.S. jobs by 2035 while growth elsewhere creates about 41 million, according to a new report from the McKinsey Global Institute

That report also notes:

> The jobs will exist, the authors argue, but it’s getting workers into them that’s the problem

Other McKinsey analysis described elsewhere finds the same pattern:

> McKinsey Global Institute's September 2026 research projects automation reducing labor demand by the equivalent of 36 million jobs in the U.S. by 2035. ... Yet broader economic growth and new AI-related roles could create over 40 million positions

2. Why it destroys jobs at the same time

Even with net gains, displacement is large and already happening:

The exposure is not even:

> The shrinking jobs are concentrated in office and administrative support, retail, and transportation, much of it lower-paid work. Lower-wage workers are 7.6 times as likely as higher-wage workers to need a new occupation

> In its base case, about 11 million workers, roughly 7% of the workforce, would need to leave their occupations entirely

Goldman Sachs research also tempers the apocalyptic view: it estimates that just 2.5% of U.S. employment would be at risk of displacement if current AI use cases were expanded

Research consistently finds AI is more likely to reshape tasks within jobs than to eliminate whole occupations outright:

> It was written by three social scientists at the UN agency who predict the new technology will likely complement and not destroy jobs by automating some tasks rather than taking over a role entirely

> Many jobs will involve new tools, faster cycles, and higher expectations rather than simple replacement

3. Why it creates jobs

> Workers with AI skills earn an average wage premium of 56% over similar roles without those skills. That's up from 25% the previous year

Revenue per employee grew 27% in AI-exposed industries vs 9% in least-exposed, funding further hiring.

4. The catch: Creation ≠ painless replacement

All reports stress a mismatch:

Historical parallel is often cited: agriculture went from majority of workforce to 1%, manufacturing from 50-60% to 5-6%— the economy created new work, but required massive reskilling and migration.

> “The next decade’s challenge is mobility, not scarcity,” they wrote

Bottom line

Whether AI is a net job creator for you depends less on the global total and more on: your industry exposure, your ability to work with AI tools (augmentation vs substitution), and access to retraining and geographic mobility.