Artificial intelligence was pitched as the great workplace equalizer, a tool that would strip away tedious tasks and free employees to focus on higher-value, more meaningful work. But new research suggests the opposite. Rather than lightening the load, AI adoption appears to be piling more on employees’ plates, leaving many feeling stretched thinner than ever.
That’s the central finding of Korn Ferry’s Workforce 2026 Global Insights Report, which paints a picture of a workforce running on fumes even as companies race to integrate AI tools across their operations.
A Workforce Stretched Beyond Its Limits
According to the report, 62% of employees say their workloads have increased significantly over the past two years. The consequences are showing: 44% of workers say they’re now stretched beyond their capabilities, and 45% report being too overwhelmed to produce genuinely meaningful results.
This isn’t happening in a vacuum. It’s unfolding alongside a sharp rise in AI adoption across nearly every industry, which makes the timing especially telling. Companies have poured resources into AI tools with the expectation that efficiency gains would follow. In some ways, 63% of employees agree that AI has made them more efficient at their jobs. But there’s a catch: 52% also say AI has increased the sheer number of tasks now expected of them.
In other words, AI isn’t just helping people do their existing jobs faster. It’s expanding the scope of what those jobs require in the first place.
Layoffs Are Cutting Jobs, Not Workload
One of the more uncomfortable findings in the report concerns the relationship between AI-driven layoffs and the work that remains. Data from outplacement firm Challenger, Gray & Christmas shows that AI has become the most frequently cited reason for job cuts since the start of 2026. Yet Korn Ferry’s research suggests this strategy may be backfiring.
The issue is one of math: AI can absorb a portion of any single employee’s responsibilities, but it cannot absorb all of them. When a role is eliminated, the tasks that AI can’t handle don’t disappear, they get redistributed to the remaining staff. As a result, 61% of employees surveyed say they’re now effectively doing the work of more than one role.
Roger Philby, Korn Ferry’s Global Lead for People Strategy and Performance, put it plainly. Piling more technology onto an already-stretched workforce, without expanding its capacity, isn’t a viable growth strategy. The organizations poised to come out ahead are the ones willing to redesign roles from the ground up. They also rethink how work actually gets done in an AI-enabled environment, and help employees see the tangible impact of their efforts.
What Redesigning Work Actually Looks Like
Korn Ferry’s report makes clear that AI’s greatest value to a business was never headcount reduction. Its real strength lies in removing repetitive, low-value tasks so that human employees can concentrate on the things people are still better at than machines, judgment, creativity, and innovation.
To capture that value, the report urges organizations to take a more deliberate approach to job redesign. That starts with clearly mapping out which tasks need human judgment. Others can be fully handed off to AI, while some require the two to collaborate. Just as important, employees need room to figure out where AI truly saves time. Elsewhere, it may have become just another box to tick.
Lesley Uren, CEO of Korn Ferry Consulting, framed the challenge as one of enablement rather than expectation. Growth, she argues, doesn’t come from simply demanding more output from an already-exhausted workforce. It comes from giving people the space to experiment, innovate, and do their best work. Cost-cutting and restructuring might generate short-term savings, she noted. But they don’t build the kind of engagement that actually drives performance. That deeper motivation is the difference between a team doing the bare minimum and one that consistently exceeds expectations. It can’t be manufactured through spreadsheets alone.
Conclusion
The findings are a pointed reminder for organizations riding the AI wave. Technology adoption without structural change leads to burnout, not productivity. If companies want AI to deliver on its promise, the solution isn’t fewer people doing more. It means rethinking how we structure work from the ground up, so both humans and AI do what they each do best.
