Layoffs tied to AI hurt worker productivity – and the reason may surprise managers

TEXT START: Business leaders and investors face a deepening paradox: Companies are pouring more money into artificial intelligence than ever, but they’re not seeing the gains in productivity that they expect.

The Dissection

The article documents a real transitional failure: AI-driven layoffs create fear, weaken adoption, damage morale, and can reduce productivity inside firms that still depend on human cooperation. But it frames this as a management mistake rather than as the first-stage turbulence of labor substitution. It wants AI to augment workers, share gains, and preserve employment—the old economic circuit with better software attached.

The Core Fallacy

It mistakes transition friction for a refutation of AI displacement. Demoralized workers may blunt short-term productivity, but that does not eliminate the incentive to replace them. Under the Discontinuity Thesis, firms do not need AI to make every remaining worker happier or more productive; they need it to reduce the cost and necessity of human labor. The article measures the damage to the human layer while assuming the human layer remains the destination.

Hidden Assumptions

• Firms are optimizing worker productivity rather than labor cost, control, and competitive survival.
• AI’s value must appear quickly in productivity statistics or stock prices.
• Training and gain-sharing can reconcile workers with technologies that threaten their employment.
• Employee sentiment is a permanent economic bottleneck rather than a temporary constraint during conversion.
• Companies can collectively refrain from AI-led cuts without being punished by competitors.
• Mass employment, wages, and consumption remain structurally intact.

Those assumptions collapse under P1–P3: durable AI superiority, coordination failure, and the loss of economically necessary work for the majority.

Social Function

Classification: partial truth, transition management, and ideological anesthetic—with an element of elite self-exoneration.

The research may accurately identify a short-run productivity penalty from insecurity. Its social function is to tell managers that better communication, training, and gain-sharing can make AI compatible with mass employment. That relocates the problem from structural displacement to poor leadership and postpones the terminal question: what happens when workers are no longer needed regardless of how positive their sentiment becomes?

The Verdict

The article is a competent autopsy of the old system’s final operating phase, not a survival formula. Layoffs can sabotage current AI productivity, but they also reveal the underlying direction: companies are attempting to sever labor from value creation. The morale crisis is not the death of AI; it is the human nervous system registering that its economic role is being removed.