Meredith Whittaker suggests that "AI" has become a convenient pretext for job cuts. Announcing layoffs as part of an "AI strategy" allows companies to frame downsizing as innovative progress to investors and the media, rather than admitting to weakening market demand.

Many tech companies publicly blame AI for workforce reductions. However, the real drivers are often post-COVID hiring bloat and a renewed focus on free cash flow after market valuations reset. AI serves as a convenient, forward-looking excuse for fundamental business corrections.

AI provides a powerful narrative for layoffs. Executives can avoid admitting poor business performance by claiming AI-driven efficiency gains, which investors may reward. Simultaneously, it gives the public a tangible, non-human entity to blame for job market instability, making it a universally useful scapegoat.

Firms are attributing job cuts to AI, but this may be a performative narrative for the stock market rather than a reflection of current technological displacement. Experts are skeptical that AI is mature enough to be the primary driver of large-scale layoffs, suggesting it's more likely a convenient cover for post-pandemic rebalancing.

Businesses are increasingly framing necessary, performance-driven layoffs as a proactive AI strategy. This shifts the narrative from business struggles to forward-looking innovation, which is a better look for investors and the public.

When CEOs announce large layoffs and attribute them to AI-driven efficiencies, it's often a more palatable narrative than admitting to strategic errors like over-hiring or misjudging demand. Claiming to be leveraging AI makes the leadership look forward-thinking and can boost the stock price, whereas admitting mistakes does the opposite.

Current tech layoffs are misattributed to AI. The real causes are the "wild" hiring binges during the zero-interest-rate COVID period and the rapid increase in the cost of capital. Companies are now correcting for that bloat, using AI as a "silver bullet excuse" for cuts that were financially necessary anyway.

While companies cite AI when announcing layoffs, the data shows cuts are concentrated in industries that over-hired post-pandemic. Job losses in sectors like tech and professional services represent a "reversion to the mean" trendline, countering the narrative that AI is already replacing workers at scale.

Skeptics argue Block's 40% layoffs are less about an AI revolution and more about covering for years of over-hiring. The term 'AI laundering' describes blaming technology for difficult business decisions that were necessary anyway, offering a more palatable public narrative than admitting to strategic errors.