Behind the AI Bubble: The '10%' Driving Growth and the Fading Workforce_Last Week's Market Summary
While the U.S. economic growth rate is reported at 1.8% as of 2025, prominent investor Steve Eisman points out that almost all of it is being driven by large-scale AI-related investments (CapEx). In other words, while the massive tech companies supporting AI are becoming the source of economic growth, other industries and workers are stagnating. This is a classic example of a 'K-shaped economy,' and serious social distortions are emerging in the shadow of the AI boom.
1. The Structure of the AI Bubble: 'Nearly 100%' of GDP Growth is Investment by Tech Companies
Eisman emphasizes that current U.S. GDP growth is 'completely dependent on AI infrastructure investment.' Companies like OpenAI, NVIDIA, and AMD are pouring vast amounts of capital into data centers, semiconductors, and model development, but it is difficult to say these are yet generating reliable returns.
He states the following:
'If this AI capital expenditure does not generate a high return on investment in the future, current stock price levels cannot be justified.'
While AI is certainly driving the market, its effects are limited, and in the real economy, the 'stagnation of non-tech industries' is becoming more pronounced.
2. 'Screams from the Front Lines': The Reality of AI Adoption and Employee Burden
During the broadcast, Eisman introduced a long email from a software developer named Max. His confession symbolizes the 'human cost' of the AI boom.
'We are being "forced" to use AI tools. Instead of increasing efficiency, we are spending more time than before fixing the errors that AI produces.'
According to Max, in many companies, the use of AI tools has become 'mandatory,' and usage rates (token consumption) have become a management metric. As a result, employees are required to 'look like they are using AI' rather than focusing on productivity, leading to a proliferation of meaningless projects and reports.
He concludes by saying:
'Leaders are forcing AI into every task and losing sight of reality. This is an illusion like "The Wizard of Oz."
This reality shows that behind the AI investment boom, the front lines are being exhausted.
3. The 'Betrayal' of the Younger Generation: Unemployment and Loss of Opportunity
What Eisman is particularly concerned about is the 'rise in youth unemployment.' While the overall U.S. unemployment rate is at a low level of around 4.5%, it has reached 11% for the younger generation (early 20s).
'Kids believed that if they learned computers, they would have jobs, so they studied engineering. However, AI has blocked that path.'
What AI has automated is precisely the entry-level work that new graduate engineers were supposed to handle. The timing of supply and demand is completely out of sync, and the phenomenon of 'AI evolving too fast' is destroying the structure of the education and employment markets.
4. The Sustainability of the 'AI Boom' and Social Risks
The frenzy of AI investment continues, but for companies to justify such high CapEx, they need 'tangible benefits.' If ROI (return on investment) does not follow, companies will eventually be forced to face pain beyond just cutting labor costs. Eisman emphasizes the risk that some AI-related spending will become 'expensive failures.'
Furthermore, the concern that the introduction of AI will undermine the 'happiness of workers' and the 'meaning of labor' cannot be ignored. Voices from the front lines like Max's, which do not welcome the introduction of AI, are already creating distortions in many corporate cultures.
Conclusion: How to Balance the Benefits and Costs of AI
To borrow Eisman's words, 'The AI economy is real, but its impact is not equal.'
While AI is helping some companies and investors build vast wealth, workers and young people on the front lines are being deprived of opportunities. This is not just a technology issue; it is a mirror reflecting the very structure of social division.
For AI to truly enhance 'human productivity,' companies must move beyond short-term thinking regarding return on investment and steer toward a 'human-centric AI strategy' that includes talent development and job redesign.
