The U.S. economy dances between "prosperity and unemployment"

In contemporary American economy, a striking phenomenon is quietly unfolding: total corporate sales continue to reach new highs, while the unemployment rate is showing a rare rise trend. This divergence is not coincidental, but rather a result of the interplay between technological advancements and labor market dynamics. According to data from the U.S. Bureau of Labor Statistics (BLS), by August 2025, the unemployment rate rose to 4.3%, a slight increase from 4.2% in July, while the Chicago Fed's preliminary estimate for October indicates that this figure may further climb to 4.35%. Meanwhile, total sales for U.S. manufacturers reached $608.27 billion in August 2025, with a month-over-month rise of 0.88% and a year-over-year increase of 1.8%. This comparison highlights the structural transformation within the economy: productivity and sales are rapidly rising driven by technology, but employment positions have not been able to keep pace.

This article will analyze the causes of this divergence based on historical data and the latest statistics, explore the role of automation, especially artificial intelligence (AI), in it, and assess its impact on the future economy.

The Unusual Discrepancy Between Sales and Employment: The First Major Shift in 20 Years

Over the past 20 years, there has typically been a high positive correlation between total sales in the U.S. trade and manufacturing sectors and the inverted unemployment rate (which reflects improvements in employment by flipping the unemployment rate curve): sales growth often accompanies job expansion, and vice versa. This relationship stems from the fundamental logic of Keynesian economics, which posits that demand drives production, thereby stimulating employment. However, since 2022, this pattern has experienced a historic rupture. According to the Manufacturing and Trade Inventories and Sales report (MTIS) from the U.S. Census Bureau, in July 2025, the actual sales total (calculated in 2009 constant dollars) for the U.S. manufacturing and trade industries reached $1,556.742 billion, growing approximately 2.5% year-over-year, marking a post-pandemic high. During the same period, the unemployment rate gradually climbed from 3.5% in 2022 to 4.3% in 2025, representing not only the most significant divergence in the past 20 years but also indicating that companies are beginning to achieve “decoupled growth” through technological means.

The quantitative analysis of this divergence shows that its magnitude has exceeded the peak after the 2008 financial crisis. The records from the Federal Reserve Economic Data (FRED) database indicate that in the first half of 2025, the total sales in trade and manufacturing cumulatively rose by 5.2%, while the inverted unemployment rate decreased by 0.8 percentage points, suggesting that the job market failed to capture the benefits of sales expansion. Economists attribute this to a “shift in the production function”: businesses have significantly increased output per unit of labor by optimizing processes through automation equipment and software. According to the Federal Reserve's report on industrial production and capacity utilization, the industrial production index in August 2025 was 103.92 (with 2017 as the base year of 100), rising by 0.9% compared to the same period in 2024, and is close to historical highs. This indicates that the U.S. economy has reached unprecedented levels in the production of goods and services, yet has not translated into widespread employment opportunities.

Further examination of the spatial and temporal distribution of divergences shows that this phenomenon is primarily concentrated in large enterprises. In the first quarter of 2025, U.S. corporate profit reports indicated that the total sales of companies in the S&P 500 index (representing 50% of the U.S. job market and 90% of corporate revenue) rose by 12.3%, but their total employment only slightly increased by 0.4%. In contrast, small enterprises (companies with a market value of less than $2 billion) experienced a sales rise of only 3.1% and a contraction in employment of 1.2%. This asymmetry reflects the threshold effect of technology adoption: large enterprises have more resources to invest in automation, while small enterprises face funding and technological barriers.

Precedent in the Industrial Sector: Employment Collapse Under Production Peaks

The industrial sector provides the clearest reflection of this divergence. Since 1980, although the U.S. industrial production index has faced the shocks of globalization and supply chain outsourcing, it has shown an overall rise. According to the Federal Reserve, the industrial production index in July 2025 is 103.82, which is an increase of over 80% compared to the baseline value in 1980, with the current level approaching historical peaks. This is thanks to the widespread adoption of advanced manufacturing technologies, such as the use of robotic arms and CNC machine tools, which have increased output efficiency by more than three times per unit input. However, in stark contrast, industrial employment continues to shrink.

According to the BLS Employment Situation Summary report, in August 2025, employment in the U.S. manufacturing sector was 12.8 million, a decrease of 12,000 from the previous month, with a cumulative decline of 78,000 for the entire year. Since its peak of 19 million in 1980, manufacturing employment has shrunk by about 32%. This “decoupling” is not sudden but rather a result of gradual technological replacement. For example, in the automobile manufacturing sector, robotic welding lines have reduced the labor hours required per vehicle from 40 hours in 1980 to 8 hours in 2025. The National Association of Manufacturers (NAM) report indicates that the number of job vacancies in manufacturing in August 2025 was 409,000, a decrease of 29,000 from July, but hiring demand is mainly focused on high-skilled engineers rather than frontline workers.

The performance of the industrial stock market further corroborates this trend. The Dow Jones Industrial Average (DJIA) rose by 15.2% in the first half of 2025, with the industrial sub-sectors (such as machinery and chemicals) increasing by 18.4%, reaching a new high in 20 years. This reflects investors' optimistic expectations about automation efficiency: companies have reduced labor costs through technological investments, with profit margins rising from 7.5% in 2020 to 11.2% in 2025. However, the cost of this prosperity has been social instability. The loss of industrial jobs has exacerbated income inequality in the Midwest 'Rust Belt,' with the Gini coefficient in the region rising to 0.48 in 2025, 5 percentage points higher than the national average. This has also indirectly fueled political polarization and social unrest, as evidenced by the prominence of manufacturing revival issues in the 2024 elections.

The Parallel Prosperity of the Stock Market and Unemployment Rate: A Rare Historical Occurrence

What is even more alarming is that the prosperity of the stock market coincides with a rise in the unemployment rate, which is extremely rare in history. The S&P 500 index has a year-to-date return of 18.38% as of October 2025, with a price return of 17.15% and a dividend return of 1.22%. This performance surpasses the 24.2% peak of 2023, mainly driven by the technology and industrial sectors. However, during the same period, the unemployment rate rose from 4.1% to 4.3%, with an average monthly non-farm employment growth of only 120,000, well below the pre-pandemic level of 180,000.

Historical data indicates that this “prosperity-unemployment” parallel has only occurred twice, at the end of the 1990s internet bubble and in the early 2000s, each time followed by market adjustments. The FRED database shows that since 1950, there have only been 5 years when the S&P 500 had annual returns exceeding 15% while unemployment rose, and the average subsequent 12-month market correction was 10%-15%. The scenario for 2025 is more complex: inflation is stable at 2.5%, the Federal Reserve's benchmark interest rate remains at 4.75%-5%, and there are clear signs of an economic soft landing, yet this has not translated into a rebound in employment. This suggests structural factors—technology-driven cost savings—that allow companies to achieve profit growth without relying on labor expansion.

The performance of the small-cap stock market is more in line with labor market realities. The Russell 2000 index (a benchmark for small-cap stocks) has returned only 8.7% from 2025 to date, significantly lower than the S&P 500, and cumulative returns have declined by 5.2% since 2021. Analysis by Vanguard shows that the earnings growth rate for small-cap stocks has fallen from 12% in 2021 to 4.5% in 2025, which is highly correlated with the rise in unemployment rates. This indicates that small businesses (which account for 60% of U.S. employment) are more susceptible to fluctuations in labor costs and cannot buffer shocks through automation like larger companies.

AI Penetration into the Service Industry: The Next Frontier of Automation Wave

The automation of the industrial sector has become a foregone conclusion, and the rise of artificial intelligence (AI) is pushing this wave into the service industry—an employment sector that accounts for 80% of the U.S. economy. The service industry includes financial services, retail, and professional services, which have traditionally relied on labor-intensive work, but AI's generative models (like GPT-5) are reshaping their production paradigms. According to the World Economic Forum (WEF) Future of Jobs Report 2025, AI is expected to replace 85 million jobs by 2027, while simultaneously creating 97 million new jobs, resulting in a net gain of 12 million. However, the replacement effect is more pronounced in the short term: Goldman Sachs estimates that 6%-7% of U.S. white-collar jobs (such as data analysis and customer service) will disappear due to AI automation by 2025.

CEO survey data reinforces this expectation. The KPMG 2025 Global CEO Outlook report shows that 79% of CEOs say AI has prompted them to reassess their employee training strategies, and 71% see AI as the main driver of workforce transformation in the next three years. Forbes' 2025 C-Suite Executive Survey further points out that 94% of respondents predict that AI will eliminate less than 5% of jobs in the next two years, but 59% believe that AI will ultimately enhance overall productivity. PwC's 2025 Global AI Employment Outlook optimistically indicates that jobs with high exposure to AI have a salary growth rate of 4.2%, higher than the average of 2.8%, suggesting that technology can “add value” to the workforce rather than simply replace it.

The surge in reskilling programs is a barometer of this transformation. The Udemy 2026 Global Learning and Skill Trends Report shows that registrations for AI-related courses are expected to rise fivefold in 2025 compared to 2024, exceeding 11 million, covering both corporate employees and individual learners. A survey conducted by the edX platform in 2025 indicates that 53% of workers plan to initiate reskilling in the next six months, and 52% believe that a comprehensive skill overhaul is necessary to cope with the impact of AI. The WEF predicts that by the end of 2025, 50% of employees will need reskilling, with key areas including machine learning and data ethics. These investments reflect a consensus among businesses and individuals: AI is not a job killer, but a productivity amplifier. In the industrial sector, machines do not completely replace human labor; rather, they enable one person to operate multiple devices, increasing output by 4-5 times. AI in the service industry may be similar: an AI-assisted financial analyst can handle the workload equivalent to that of 4-5 people.

The Awkward Reality of Current AI Implementation: High Investment, Low Return

Despite optimistic expectations, the actual deployment of AI faces bottlenecks. The 2025 Generative AI report update from MIT shows that 95% of enterprise AI pilot projects fail to generate a return on investment (ROI), mainly due to high infrastructure costs and integration challenges. The report analyzed 500 companies and found that only 5% of projects achieved rapid revenue acceleration, while the majority are stalled at the proof-of-concept stage. In budget allocation, over 50% is spent on sales and marketing tools, but the highest ROI is seen in logistics automation, such as supply chain optimization, with efficiency improvements of 15%-20%.

Small businesses experience a stronger sense of frustration. A Gallup survey from 2025 shows that 55% of small and medium-sized business owners regret replacing human labor with AI, citing training costs (an average of $5,000 per employee) and output not meeting expectations. In contrast, while large enterprises invest billions of dollars in AI infrastructure (for instance, Meta's capital expenditure is projected to account for 36%-38% of revenue in 2025), short-term ROI remains equally bleak. The BCG 2025 AI Workplace Report indicates that the adoption rate of AI in businesses has reached 94%, yet only 30% report productivity improvements, with the remainder largely attributed to the “silicon ceiling” effect—frontline employees struggle to overcome technological barriers.

Large vs. Small Enterprises: A Magnifying Glass on the Discrepancies

The divergence between large S&P 500 companies and the labor market is particularly prominent. These companies account for 90% of U.S. corporate revenue, with a sales rise of 14.9% in the second quarter of 2025, while employment only increased by 0.5%. The Russell 2000 small-cap stocks are projected to see a decline in earnings by 2.1% in 2025, aligning with a drop in the unemployment rate. Vanguard predicts that small-cap stocks will lag behind large-cap stocks by 1.9 percentage points in annualized returns over the next 10 years, primarily due to high financing costs and delayed technology adoption.

An analysis of large tech giants shows that profit expansion is largely due to non-AI factors. NVIDIA's revenue for fiscal year 2025 is $130.5 billion, rising 114%, primarily from high pricing of data center chips, with a gross margin of 75%. Meta and Alphabet enhance profits through advertising optimization, with Meta's operating profit margin rising to 28% in 2025, and Alphabet's cash flow increasing by 13.2%. Amazon's revenue comes 80% from AWS cloud services and advertising, which are non-AI core. Microsoft's software business has low marginal costs, with revenue growth following scale expansion, and is projected to grow by 14.9% in 2025. These companies' AI spending reaches hundreds of billions, but it has not translated into cost savings; instead, AI infrastructure has become a new cost center.

In summary, the U.S. economy is at a technology-driven crossroads: record sales and production, but employment is lagging, creating a rare divergence not seen in 20 years. The industrial sector has completed its automation transformation, and the service industry is following the wave of AI. The latest data shows that industrial production will remain high in 2025 while employment continues to shrink; the prosperity of the S&P 500 masks the mirror image of small-cap stocks and unemployment rates. CEO surveys indicate a reconfiguration of the workforce, but an MIT report warns of implementation bottlenecks. Profits of large enterprises are not due to AI, while small businesses struggle to survive.

Short-term risks are prominent: AI-related stocks (such as NVIDIA) are experiencing a valuation bubble, with a P/E ratio of 60 times in 2025, far exceeding the historical average of 35 times. If ROI remains sluggish, market adjustments could trigger a chain reaction in employment, with Goldman Sachs warning of a 6%-7% job loss. In the long term, AI reskilling is expected to unleash $4.4 trillion in productivity potential (according to McKinsey), but policy intervention is required: government subsidies for retraining and tax incentives for fair automation transitions. Otherwise, disparities will exacerbate inequality and threaten economic stability.

Looking ahead to 2026, if the Federal Reserve continues to cut interest rates, small-cap stocks may bounce back by 10%, but the risk of an AI bubble burst reaches 30%. Companies need to balance investment and manpower, and employees should embrace reskilling. Technology is not the enemy, but a mirror reflecting the need for a more inclusive future in the economy.