Is AI turning you into a “frontrunner” or are you working in the “engine room?”
A huge survey carried out by consulting giant PwC found that AI is allowing a small group of workers to pull away from the rest of the workforce and dividing employees into four distinct categories.
The Big Four firm published its “2026 Global Workforce Hopes and Fears Survey” on Tuesday. It surveyed almost 50,000 workers across 48 countries and 29 sectors between May and June 2026.
AI use is rising, the survey found. 64% of workers said they had used AI at work in the past 12 months, up 10 percentage points from a year earlier, and the share using generative AI every day rose from 14% to 22%.
But the survey revealed a widening divide in how workers are getting the tools and opportunities to benefit from AI.
Based on the responses, PwC identified a group it called “front-runners,” which make up 14% of those surveyed.
The front-runners have in-demand skills and reported getting strong benefits from AI in their work. Just over half the group use generative AI daily, while nearly 80% said they have access to learning and development resources.
Then there’s what PwC calls the “engine room” workers — 56% of workers who PwC characterizes as the core of organizations’ day-to-day delivery.
Just a small number of these workers say they use generative AI daily, and fewer than 40% say they have access to learning and development resources.
“They’re not getting the same access to learning. They’re not getting the opportunity to innovate. They are not getting to use AI in a meaningful way,” said Peter Brown, PwC’s global workforce leader.
PwC’s third category is “AI insurgents,” who make up around a fifth of staff. Their skills are less in demand than those of front-runners, but they’re ambitious in how they use AI.
Finally, there are the “indispensables,” who have scarce skills that are highly valued by employers.
The outcome of this divergence showed up in findings on job security, workers’ confidence in asking for a promotion, trust in managers, and skills development — all of which were lower for the engine room cohort.
The divergence between the groups is creating a “two-speed” workforce, said Brown.
The survey does not establish the reasons behind workers’ experiences, and PwC’s worker categories are partly based on respondents’ reported experiences with AI and on how in demand they believe their skills are.
Still, the findings point to a practical challenge for employers spending heavily on the technology and seeking ROI: buying tools is not the same as changing work across an organization.
Ignoring the divide between employees risks missing out on productivity, revenue per employee, job security, and satisfaction, Brown said: “The danger is that you actually could render a big chunk of your workforce largely irrelevant in the world of work.”
PwC, one of the Big Four accounting and consulting firms, itself employs over 360,000 people globally and has raced to build internal chatbots, upskill staff, and test AI in client work.
The firm pitches itself as “client zero” for AI transformation while advising companies on how to make the same shift. While the firm has made some mistakes along the way, Brown said PwC has embraced AI, which has brought positive changes to the work and the tools employees have access to.
The changes have included rewriting PwC’s training agenda around 30 core skills: 15 AI-centric and 15 human-centric, a change introduced in February 2026. The firm has also reduced the number of offices its entry-level US consultants can join, in a bid to improve community and learning opportunities.
Brown said companies should be transparent about why they are using AI and the outcomes they hope to achieve. “Workers aren’t expecting leaders to, I think, sugarcoat everything,” he said. “They just want to understand what’s going on.”
“Leaders who display those kind of characteristics and others tend to be the ones that seem to be bringing the workforce along with them,” he added.
For employers, Brown said, widening access to AI is not an either-or choice between backing the front-runners and investing in everyone else.
The results show that “there’s an enormous amount of value there that can be tapped” if leaders can get more of the workforce to lean in, he said.
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