This Gap is About to Break the Economy…

Key Concepts

Divergence between Sales and Employment: A historic trend where total sales by US firms in trade and manufacturing sectors are at record highs, while the unemployment rate is also rising (inverted).
Industrial Production vs. Industrial Employment: US industrial production is at all-time highs, but industrial manufacturing employment has significantly declined since 1980.
AI Adoption and Workforce Transformation: CEOs anticipate significant worker replacement by AI, with AI seen as a primary driver of workforce change.
AI Reskilling: A rapid surge in AI reskilling programs for both businesses and consumers, indicating an intention to adopt AI for productivity gains.
AI Implementation Challenges: A significant percentage of businesses are not seeing a return on investment from AI implementation, and some small business owners regret replacing workers with AI.
Large Cap vs. Small Cap Stock Performance: A divergence between the performance of large-cap stocks (S&P 500) and the labor market, while small-cap stocks (US small cap stocks) have stagnated and mirrored labor market trends.
Profit Margin Drivers for Large Corporations: Profit growth in large tech companies is attributed to factors like high chip prices (Nvidia), increased ad revenue (Meta, Google), AWS and ads (Amazon), and software business models (Microsoft), rather than AI cost-cutting.
AI as a Cost vs. Cost Saver: Currently, AI is seen as a significant investment and cost for companies, with no clear short-term return on investment from automation.
AI Financial Bubble: The current AI stock market surge is likely driven by speculation and a financial bubble, with potential for a sharp unwinding.
AI Trade: A current market trend involving investment in AI-related stocks, driven by momentum, with a warning of potential violent unwinding.

Divergence in US Economic Indicators

A significant and historic divergence has emerged between the total sales of US firms in the trade and manufacturing sectors and the job market, specifically the inverted unemployment rate. For the first time in 20 years of data, corporations are achieving record sales while simultaneously laying off workers. This trend is mirrored in the stock market, which has also been thriving alongside rising unemployment, a phenomenon rarely seen historically. This indicates a fundamental shift in the economy, driven by the real-time ability of corporations to automate and streamline costs through technology.

Industrial Sector: Automation's Precedent

The industrial sector serves as a clear precedent for technological displacement of labor. Despite the US industrial production index remaining at all-time highs, reflecting record goods production, the total number of employees in the industrial sector has seen a dramatic decline since 1980. Concurrently, the industrial sector of the stock market has experienced significant growth over the past two decades, reaching record highs. This demonstrates that technological automation has already profoundly impacted industrial manufacturing employment, leading to societal disruptions such as increased wealth inequality, the rise of populism, and political polarization.

AI's Potential Spread to the Services Sector

The critical question now is whether the automation observed in manufacturing is beginning to extend to the services sector due to the advent of Artificial Intelligence (AI). Survey data from CEOs reveals a strong expectation of AI-driven worker replacement:

4 in 10 business leaders anticipate replacing workers with AI by 2026.
72% of business leaders believe AI will be the primary driver of workforce transformation in the next three years.

This sentiment is further supported by a surge in enrollments in AI reskilling programs over the past two years, indicating a clear intent from both individuals and businesses to adopt AI for productivity enhancement. The potential impact is significant, as one person utilizing AI could potentially achieve the output of four to five individuals without it, a pattern consistent with historical technological adoption where new machinery drastically increased individual output.

Current AI Implementation: Disappointing Returns

Despite the anticipation and reskilling efforts, the actual implementation of AI has yielded disappointing results so far, particularly concerning return on investment (ROI).

A MIT study indicated that 95% of businesses attempting to implement AI are not generating an ROI.
Another survey found that 55% of small business owners admitted to regretting replacing employees with AI.

When the performance of US small-cap stocks, representative of small businesses, is overlaid with the labor market, the same divergence seen with large corporations is absent. Small businesses have largely stagnated since 2021, with declining earnings, which aligns more closely with the rising unemployment environment.

Large Cap Stocks and the Divergence

The divergence between large-cap stocks and the labor market, however, remains a significant point of observation. The S&P 500, which comprises the largest US companies and represents 50% of the US job market and 90% of corporate revenue, shows a different trend. If these large corporations are successfully implementing AI, it could explain the current economic divergence.

Companies like Nvidia, Meta, Alphabet, Amazon, and Microsoft have experienced soaring profit margins and earnings. However, their hiring has not significantly increased, with notable exceptions for highly compensated AI experts. A deeper analysis suggests that the expansion of profit margins in these corporations is driven by factors other than AI cost-cutting:

Nvidia: Benefited from charging extremely high prices for its in-demand AI chips.
Meta and Alphabet (Google): Increased revenue from their advertising businesses.
Amazon: Saw most of its earnings growth from Amazon Web Services (AWS) and its advertising business, not AI.
Microsoft: Its software business inherently has low costs and sees profit margins grow with revenue.

These factors are not directly related to AI automation or cost reduction. In fact, AI has largely been an expense, with these companies investing billions in AI infrastructure without a clear short-term ROI.

The AI Financial Bubble and Future Risks

The current divergence between large-cap stocks and the labor market is therefore not attributable to AI cost-cutting. Instead, AI-related stocks are likely overvalued, running far ahead of what AI can realistically deliver in the short term. This suggests the formation of a financial bubble that is poised to unwind, potentially causing significant pain.

While technological automation is an ongoing process that will undoubtedly spread to the services sector as the workforce adopts AI skills, the immediate future for the labor market is more likely to see job losses stemming from the unwinding of this AI financial bubble rather than from actual automation.

Trading Implications and Conclusion

This scenario presents a critical consideration for traders. The current "AI trade," involving exposure to stocks like ACMR, ASML, Nvidia, and Applied Materials, has yielded impressive returns due to strong momentum. However, this momentum is unsustainable, and the AI trade is likely to unwind violently when it turns. Traders are advised to be extremely aware of this risk. For those interested in such trading strategies and insights, services like Braavos Research offer detailed trade sharing and have demonstrated significant returns.

In conclusion, while AI's long-term potential for automation and productivity is undeniable, the current economic divergence between large corporations and the labor market is not driven by AI cost savings. Instead, it appears to be fueled by a speculative financial bubble in AI stocks, which carries a significant risk of a sharp and potentially damaging correction. The real impact of AI on job displacement in the services sector may be delayed until after this bubble bursts.