The Promise vs. Reality
AI was sold as the ultimate productivity engine: faster execution, lower costs, more output with fewer people, and even a path to the four-day workweek. The data tells a different story.
According to Korn Ferry’s Workforce 2026 report (16,000 employees across 11 countries), **52% of workers say AI has increased their workload**. Meanwhile, **61%** report they are now performing the responsibilities of more than one role. CEOs remain far more optimistic: **79%** claim improved efficiencies from AI. Only about half of individual contributors agree.
Why AI Is Adding Work, Not Removing It
Organizations that treat AI primarily as a cost-cutting tool create a “super-burden” instead of superpowers:
- Structures are flattened and managers are cut; remaining managers absorb extra load while also managing AI.
- Survivors of layoffs use AI to produce more output and cover gaps—often without extra pay, title changes, or capacity support.
- The default response becomes further headcount reduction, squeezing the remaining workforce harder.
U.S. data sharpens the picture:
- 43% of managers say they are too busy to deliver meaningful results.
- 44% report their company has laid off managers.
- Half feel exhausted by the pace of change.
- 62% of U.S. workers say they now handle more than one role.
- 53% say AI tools have increased the number of tasks expected in their role—even as 61% acknowledge AI improved their personal efficiency.
Efficiency gains and workload reductions are not the same thing. When organizations simply layer AI onto existing systems and demand more output from fewer people, the technology becomes another source of pressure rather than relief.
When AI Actually Works
The difference is people strategy, not technology alone.
- **IKEA** deployed an AI chatbot that handled nearly half of customer queries, then reskilled 8,500 call-center employees into interior design roles—creating new value instead of discarding talent.
- **Walmart** is pairing its large-scale AI push with deliberate investment in reshaping work, leadership, and purpose for its 2.1 million employees.
AI delivers productivity only when organizations invest equally in the people who use it. That means reskilling, fair compensation for expanded scope, capacity and well-being support, and giving employees the authority to redesign their work. Without those elements, AI does not lighten the load—it multiplies it.
Productivity is not a boardroom metric. It is felt (or not felt) in the day-to-day experience of the people doing the work.