Will AI create or take away more job opportunities?

This is a topic where perspectives are still evolving and data is being updated frequently by major institutions, so let me look up some current analyses.## The short answer: Most major forecasts predict AI will create more jobs than it destroys — but the transition is uneven, and near-term data is more mixed than the optimistic long-term projections suggest.

The optimistic macro view

The most widely cited projection comes from the World Economic Forum's Future of Jobs Report 2025, which surveyed predicts that mainly due to technological changes, this decade will see the creation of 170 million new jobs, offset by the displacement of 92 million positions, resulting in a net increase of 78 million jobs. That report also found by 2030, AI and other information processing technologies will transform 86% of businesses, sparking the creation of 170 million new roles worldwide while making 92 million existing jobs redundant.

McKinsey's estimate is similarly upbeat: McKinsey Global Institute gives an optimistic estimate for AI job creation. According to McKinsey, AI could contribute to the creation of 20 to 50 million new jobs globally by 2030.

A U.S.-focused analysis from ITIF reinforces this, arguing that the evidence tells a clear story: the employment gains from AI and the data center buildout dwarf the displacement effects from automation. That analysis noted outplacement firm Challenger, Gray & Christmas estimates that approximately 12,700 jobs were lost due to AI in 2024, far less than the number created by the technology, representing just 0.1 percent of all layoffs that year.

But the numbers hide real pain

Even WEF's own headline figure comes with caveats. The net gain masks massive churn: the ratio of new roles to displaced roles is 1.85, meaning the projected number of new roles is about 1.85 times the projected number of displaced roles, but displaced roles equal 54.12% of new roles, which shows why the transition cannot be treated as socially painless.

Business leaders themselves are split — and skew pessimistic in the near term: more than half of business executives globally expect the technology to displace existing jobs, while only 24% said AI will create new jobs. Separately, 41% of employers plan to reduce their workforce as AI automates certain tasks.

Public sentiment mirrors this unease: a BMG poll shows that 55% of employees think more jobs will be lost to AI than created by it.

Who's actually being hit right now

The pain isn't evenly distributed. Young, entry-level workers appear especially vulnerable: employment for AI-exposed 22-to-25-year-olds fell roughly 16% according to Stanford Digital Economy Lab (2026). Similarly, a decline in entry-level hiring for AI-exposed white-collar jobs has been highlighted, with 6–7% of U.S. workers potentially facing AI-related job losses, mainly white-collar workers.

WEF's own qualitative work captures this asymmetry well, describing how a customer service centre that once employed 500 people might transform into 50 AI oversight specialists working from a single location — a real net loss for that specific group, even if new jobs appear elsewhere.

Where new jobs are actually showing up

Concrete evidence of job creation is emerging in the U.S.: The Economist tracked engineers, software developers, mathematicians and data scientists and estimated those occupations added roughly 730,000 jobs above the broader trend in professional employment since 2022. Additionally, LinkedIn separately estimated roughly 640,000 new AI-specific jobs were created between 2023 and 2025. Growth is also spreading to infrastructure: the BLS projected utilities would be the fastest-growing major U.S. industry sector from 2025 through 2035, increasing employment 9.8%, or 58,800 jobs, nearly all in electric power generation, transmission and distribution because of rising electricity demand, including demand from AI.

The bottom line

Most rigorous long-term forecasts (WEF, McKinsey, ITIF's analysis of 2024 U.S. data) point toward net job creation by 2030, driven by new AI-specific roles, infrastructure buildout, and demand in adjacent fields like cybersecurity and renewable energy. However:

In short: the aggregate numbers favor "more jobs created," but that's a poor guide to individual experience — plenty of specific workers and occupations will genuinely be worse off, even as the economy as a whole adds net positions.