The 'Super-Burden' Effect: Why AI is Adding Tasks Instead of Saving Time for 52% of Workers

The moment an organization decides to deploy artificial intelligence without simultaneously redesigning its job roles is the moment the technology stops saving time and starts creating it. When new tools are layered on top of existing responsibilities rather than replacing them, the anticipated productivity gains evaporate into administrative friction. That structural failure is now showing up in the data: according to a new global survey of 16,000 professionals, 52% of workers report that AI has actually increased the number of tasks expected of them.[1][4]

The findings, published in Korn Ferry's Workforce 2026 Global Insights Report, highlight a growing disconnect between the promise of automation and the reality on the ground. Across 11 countries, 62% of employees say their workloads have grown significantly heavier over the past two years. Rather than freeing up schedules for high-level strategy, the current implementation of AI is leaving 45% of workers too busy to deliver meaningful results, and 44% feeling stretched entirely beyond their capabilities.[2][4]

The data reveals a distinct paradox in how the technology functions. When employees use AI for a specific, targeted task, 63% agree that it genuinely improves their efficiency. The technology itself works. The breakdown occurs in how organizations respond to that newfound efficiency: rather than allowing employees to bank the saved time for deep work or innovation, companies are immediately filling the gap with additional tasks and higher baseline expectations.[2][4]

This dynamic is fundamentally a question of who captures the value of saved time. In freelance and independent work, professionals who use AI to complete tasks faster can take on more clients or simply work fewer hours, keeping the margin for themselves. Inside traditional corporate structures, however, the time saved by an employee is quickly absorbed by the employer, translating into a denser, faster-paced workday without a corresponding increase in compensation or title.[3]

The pressure is compounded by widespread corporate restructuring. As companies adopt AI, many have flattened their hierarchies and reduced headcount to cut costs. Korn Ferry notes that while AI can eliminate specific repetitive tasks, it cannot absorb the entirety of a laid-off employee's workload. The remaining responsibilities are inevitably redistributed among the surviving staff.

Consequently, 61% of surveyed workers now report that they are effectively performing the responsibilities of more than one role. When employees are forced to manage these expanded portfolios while simultaneously learning to integrate new AI tools into their workflows, the result is what researchers describe as a "super-burden"—a state where high activity masks a severe drop in actual productivity.[1][4]

The perspective on this shift varies wildly depending on where one sits in the organizational chart. Among CEOs, 79% report that AI has successfully improved efficiencies within their companies, often pointing to the technology's ability to synthesize messy data into actionable insights. But among individual contributors, only 51% share that view, highlighting a massive blind spot in how executive leadership perceives the daily friction of AI adoption.[1][4]

Middle managers, traditionally the bridge between executive strategy and frontline execution, are bearing the brunt of this transition. The survey found that 42% of organizations have eliminated management roles over the past year. Of the managers who remain, 55% report feeling exhausted by the pace of change. This hollowing out of the management tier leaves 39% of workers feeling directionless, lacking the guidance needed to navigate their expanded roles.[2][4]

Yet, those remaining managers are critical to making AI work. Just over half of the workers surveyed credited their direct managers with encouraging the kind of experimentation necessary to figure out where AI actually adds value. Experts argue that workers need the space to discover the technology's utility organically, rather than having it mandated as a top-down directive to simply "do more."[4]

Fixing the productivity paradox requires a fundamental shift in corporate strategy. "Growth doesn't come from just asking people to do more. It's about enabling them to do their best work, with space to experiment and innovate," said Lesley Uren, CEO of Korn Ferry Consulting. Organizations that successfully integrate AI are those that actively redesign jobs—explicitly mapping out which tasks require human judgment, which can be fully delegated to software, and how the two interact to drive actual growth.[4]