Nearly half the world's workers fear being left behind by artificial intelligence — and the newest global evidence suggests they are right to worry. PwC's 2026 Global Workforce Hopes and Fears Survey, published on September 29 and covering nearly 50,000 workers across 48 countries and regions, finds a workforce splitting into two camps: a minority of AI “front-runners” pulling ahead, and a majority at risk of being stranded as the technology accelerates.
The headline finding is a paradox. Across the workforce, AI use is up 10 percentage points — yet access to learning and development resources is down 8 points. Workers are being asked to adapt faster while being given less help to do it. For employers, the survey carries a blunt warning: companies risk losing the very AI-savvy employees they most need, while leaving the majority behind.
A workforce dividing in two
The divide runs through the middle of the labour market. Overall, just 51% of workers say they have access to the learning and development resources they need — down from 59% last year. But the pain is concentrated among the 56% of “engine room” workers whose skills are less scarce and who are not far along the AI learning curve: only two in five of those workers say they have the training resources they need.
Meanwhile, workers who use AI daily paint a strikingly different picture. They are significantly more likely to trust management, feel secure in their jobs, and view technological change positively. The technology itself is not the divider — access to it, and to the training that makes it useful, is.
The front-runners are pulling away — and thinking of leaving
The survey's most uncomfortable finding for employers concerns the people they can least afford to lose. Almost a third — 29% — of “front-runner” employees with strong AI capabilities and scarce skills say they are very or extremely likely to change employer in the next year. These are the workers who use AI every day, who have the skills the market is bidding up, and who know it.
The dynamic is a slow-motion retention crisis. Companies underinvest in developing their AI-capable staff, those staff grow confident in their market value, and competitors — many of them desperate for the same scarce skills — come calling. The cost of replacing a front-runner vastly exceeds the cost of developing one, yet development budgets are moving in the wrong direction.
“Workers are under growing pressure from rising workloads, rapid change and external uncertainty. But those using AI every day are more confident, more ambitious and more positive about their careers and prospects. The challenge for leaders is to keep developing those people – but not at the expense of the rest of the workforce.” — Pete Brown, Global Workforce Leader, PwC
The cost-of-living squeeze
The AI divide is unfolding against a backdrop of real financial pressure. Only a third of workers report having money left at the end of the month — down 8% year on year. Almost a third (29%) say they have significantly less bargaining power than three years ago, more than double the number who disagreed. For fully remote workers, the proportion reporting lost bargaining power is 10 points higher still.
This matters because financial stress and skills anxiety feed each other. Workers who cannot afford to take time off for training, or who fear that asking for development marks them as dispensable, fall further behind — while their more secure colleagues compound their advantage. The divide is not only about technology; it is about who can afford to adapt.
Why employers are getting this wrong
Part of the problem is structural. Separate research from Payscale, previewed on September 24, found that talent management systems have failed to keep up with AI-driven change: 61% of organisations say they are rewriting job descriptions because of AI, but only 48% say their market benchmarking reflects the skills those roles now require, and 49% of employers report their salary structures have not kept pace.
In other words, companies are redesigning roles around AI faster than they can price, support, or staff them. Training budgets — often the first cut in a downturn and the last restored in a recovery — have not caught up with the pace of change on the ground. The result is a workforce strategy built for a slower era.
What employers should do
The survey points to a clear agenda for business leaders:
- Extend AI training to the majority, not just the stars. The 56% of “engine room” workers are where the biggest gains — and the biggest risks — sit. Broad-based AI literacy programmes pay for themselves in productivity.
- Fix the development deficit first. With L&D access down 8 points in a single year, restoring training budgets is the fastest lever available. Workers who use AI daily trust management more; giving more workers that experience builds the trust companies need for further change.
- Retain the front-runners deliberately. When 29% of your most AI-capable people are considering leaving, retention is a board-level issue. Career paths, pay progression, and meaningful AI work matter more than perks.
- Address the cost-of-living reality. Financial stress undermines learning. Pay structures that have not kept pace with AI-driven role changes need urgent review.
What workers can do
For individuals, the survey's message is empowering as well as sobering: the workers thriving are not necessarily the most senior or the most credentialed — they are the ones using AI every day. Practical steps include:
- Make AI a daily habit. The confidence gap in the survey tracks usage, not job titles. Regular hands-on practice with AI tools is the single strongest predictor of feeling secure.
- Ask for training — specifically. Generic requests get ignored; specific ones (“I need access to the company's AI upskilling programme”) are harder to refuse, especially when 74% of employers say they plan AI upskilling investment.
- Document AI-augmented results. As employers rewrite job descriptions around AI, evidence of what you have delivered with these tools becomes promotion and pay-rise currency.
- Build scarce, complementary skills. Judgment, domain expertise, and the ability to direct AI systems are what the market is bidding up — routine execution is what it is automating away.
The AI skills divide is not destiny. But PwC's data makes one thing clear: left to drift, the gap widens — and the workers and companies that act deliberately are the ones that end up on the right side of it.
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