AI is not creating one uniform experience of work. It is creating distinct paths for workers, and leaders will determine how far apart those paths become.
That was the central message from Peter Brown, Global Workforce Leader at PwC, in an interview with UC Today at Unleash Paris. Drawing on PwC’s recent AI Jobs Barometer and Global Workforce Hopes and Fears Survey, Brown warned against assuming every employee starts their AI journey from the same place.
What Does PwC’s Research Say About the AI Workforce Divide?
PwC’s research points to a labor market splitting between roles that AI strengthens and those where it increasingly standardizes routine work.
Key findings include:
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Professionalized roles are growing twice as fast as AI-democratized roles, according to PwC’s 2026 AI Jobs Barometer. PwC reported that professionalized roles have seen 42% faster average salary growth than democratized roles.
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PwC’s Global Workforce Hopes and Fears Survey identified front-runners as 14% of the workforce. These employees have in-demand skills, access to development, and greater confidence experimenting with AI.
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The survey classifies 56% of workers as the “engine room.” These employees run customer service and operations, yet often report less access to training and less clarity about AI’s impact on their role.
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The Hopes and Fears survey drew on responses from 49,364 workers across 48 countries and regions, PwC said.
Brown said the AI Jobs Barometer draws on nearly a billion job advertisements to ground the conversation in labor-market evidence, rather than speculation.
Peter Brown, Global Workforce Leader at PwC, said:
“We’re seeing this divergence in terms of what we call professionalized roles and what we call democratized roles.”
Why Could AI Create a Two-Speed Workforce?
A two-speed workforce emerges when AI creates new opportunities for some employees while others do not get the access, skills, or leadership support to benefit.
In professionalized roles, Brown said AI can remove routine tasks and free people to focus on higher-value work. He pointed to legal work as one example. In more democratized roles, such as inventory clerks, AI may take on routine work without necessarily creating the same uplift in differentiation or pay.
The risk is not that jobs change. Jobs have always changed. The issue is the speed of change and whether leaders bring employees with them.
Discussing the divide, Peter Brown, said:
“Unless there’s leadership action, recognizing that not everybody starts in the same place in the workforce, then that gap, that skills gap, that experience gap, yes, technology gap, will increase.”
How Should Leaders Close the AI Skills Gap?
Brown’s advice centers on work redesign rather than simply adding another tool to an existing process.
Leaders should start with a specific business challenge, then decide how people and technology can work together to solve it. PwC’s research indicates that organizations which bolt AI onto old workflows often fail to achieve the results they expect.
Brown highlighted three practical priorities:
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Start with the business problem. Choose a focused challenge, redesign the workflow, and measure the outcome before scaling.
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Meet employees where they are. Assess different levels of AI familiarity and provide relevant, role-specific training.
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Communicate with clarity. Workers do not expect leaders to have every answer, Brown said, but they do expect honest direction and transparency.
This also matters for early-career employees. AI may remove some traditional learning-by-observation tasks, but Brown said organizations can deliberately redesign work to develop problem-solving, empathy, and critical-thinking skills.
Final Takeaway
The AI workforce gap is not inevitable. It is a leadership problem before it becomes a labor-market problem.
Organizations that treat AI as a shortcut to efficiency risk leaving much of their workforce behind. Those that redesign work, invest in tailored development, and communicate openly stand a better chance of creating growth that employees can actually share.
FAQ
What is PwC’s AI Jobs Barometer?
PwC’s AI Jobs Barometer analyzes close to a billion job advertisements to examine how AI is changing jobs, skills demand, wages, and labor-market growth.
What is a two-speed AI workforce?
A two-speed workforce describes a divide between employees who have access to AI tools, development, and high-demand skills, and those who do not receive the same support or opportunity.
What are professionalized roles?
PwC uses the term for roles where AI automates routine work and enables employees to focus on more complex, higher-value tasks. PwC’s 2026 research found these roles have grown faster and achieved stronger wage growth than democratized roles.
How can leaders reduce the AI skills gap?
Leaders should begin with a defined business challenge, redesign the related workflow, provide role-specific AI development, and communicate clearly about how roles may change.
Will AI remove entry-level jobs?
AI is changing entry-level work, but Peter Brown said employers should redesign early-career roles to preserve structured learning and develop human skills such as critical thinking, empathy, and problem-solving.
