Why most AI driven reorgs are solving the wrong problem

In February 2024, Klarna's CEO Sebastian Siemiatkowski announced that the company's AI assistant had taken over the work of 700 customer service agents, reducing staff from 5,500 to 3,800. This dramatic reduction, dubbed "AI washing," led other companies to follow suit in a misguided attempt to save costs. However, 18 months later, Klarna quietly began rehiring, as customer satisfaction plummeted and human support became necessary for tasks AI couldn't handle.

Klarna's experience illustrates a broader issue: most AI-driven reorganizations are solving the wrong problem. A Harvard Business Review study in January 2026 revealed that 60% of organizations had cut staff in anticipation of AI, but only 2% had actually replaced human roles with AI. Davenport and Srinivasan coined the term "AI washing" to describe companies using AI as a narrative to hide financial restructuring.

Companies that have successfully implemented AI-driven restructuring, like Tripadvisor and ClickUp, have focused on redesigning workflows to leverage AI for tasks it excels at, while preserving human roles for those requiring judgment, creativity, and relationship-building. These companies report three times higher chances of capturing real value from AI and twice the AI usage per employee.

This approach emphasizes designing the work around AI rather than restructuring around it. The lesson is clear: work redesign is harder, slower, and less visually appealing than structural changes, but it is crucial for long-term success. Companies must prioritize designing the work to fit AI capabilities, rather than merely reorganizing and hoping for the best.