"AI Whitewashing" Backfires: Companies Using Technology as an Excuse to Lay Off Workers Face Trust Crisis

In February, payments giant Block pioneered a new corporate communications tactic dubbed "AI whitewashing," attempting to justify mass layoffs by leveraging claims that artificial intelligence can dramatically boost productivity. This strategy proved effective in the short term, successfully driving up the company's stock price and prompting CEOs worldwide to follow suit. However, this seemingly successful deception is now backfiring. Latest indications suggest that blaming cuts on AI may no longer work and could even be producing negative effects. The so-called "AI whitewashing" refers to companies fabricating lies about revolutionary productivity gains driven by artificial intelligence while claiming to have witnessed astonishing changes within closed environments, thereby forcing them to lay off thousands of employees. Such narratives attempt to frame harsh downsizing as an inevitable outcome of technological advancement. Recently, multiple firms that followed Block's approach have found themselves in trouble; their shared characteristic was using AI as a scapegoat to mask genuine financial or managerial issues. Although markets initially reacted positively to such announcements, pushing up share prices for relevant companies, both the public and investors gradually recognized logical flaws. As enterprises repeatedly deployed the same rhetoric without delivering actual efficiency improvements, market confidence began to erode. What once aimed at polishing the image of workforce reductions through "technological storytelling" has instead triggered external skepticism regarding management integrity and technical authenticity. If "AI whitewashing" ceases to conceal reality, these companies seeking to get away with it may face intensified public scrutiny and heightened risks of declining stock valuations. This demonstrates that strategies relying solely on hype-driven concept promotion to divert attention have reached their limit; businesses must return to core operational fundamentals rather than depending on fabricated technological transformations to navigate crises.