Historically, job postings and the stock market tended to move in the same direction. Hiring, an outcome of company health and growth, drives stocks higher, while stagnant hiring or layoffs can suggest that a firm is in distress. That changed in 2023.
Throughout most of 2022, the stock market fell on concerns of high inflation and rapid interest rate hikes. In 2023, with confidence restored and investors exuberant about the productive potential of generative artificial intelligence, the stock market soared. In stark contrast to the past, job postings[1] plunged.
Using JobsEQ’s Real Time Intelligence (RTI) tool,[2] we investigated this divergence to:
- Understand whether this difference was an anomalous event or a shift in the labor market, and
- Determine the nature of such a shift
Generative AI In the Post-Pandemic Economy
A perfect storm developed in 2022 that impacted both the labor market and the stock market. With elevated inflation more stubborn than policymakers expected, the Federal Reserve started aggressively hiking rates in March 2022. The federal funds rate ended the year at a 4.25% to 4.50% target range – 425 basis points higher than the start of the year. Such aggressive tightening of financial conditions inevitably pressures firms with debt, especially those in the high growth tech sector.
The tech sector faced particular pressure to shift strategies to protect profits after going through a hiring spree in 2021 to meet the needs of an economy shifting towards pandemic-related remote work. As interest rates rose and financial conditions tightened, firms began shifting away from remote work. As a result, the hiring spree reversed. Crunchbase estimates that the tech sector saw 93,000 layoffs in 2022 and 191,000 in 2023.[3]
In November 2022, OpenAI released the generative artificial intelligence (AI) tool, ChatGPT, which immediately became synonymous with the productivity enhancing potential of large language models. Throughout 2023, additional developments in the AI space boosted markets, especially the tech sector. OpenAI released an updated model based on GPT4 in March 2023 and an enterprise version in August, which was optimized for firm-wide use.
Throughout 2023 and 2024, models such as Google’s Gemini and Anthropic’s Claude were announced and improved as tech firms rushed to make use of the emerging technology. The adoption of AI was buoyed by improvements in hardware, led by NVIDIA’s AI optimized graphics processing units (GPUs).
Unlike previous iterations of automation, generative AI enabled the automation of tasks designated for white-collar workers with high educational attainment and high salaries. The potential to cut the high-salary workforce without negatively impacting productivity in the short-run increased investor exuberance and sent stocks higher.
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[1] All job posting data is for active job posts obtained from JobsEQ® by Chmura.
[2] This tool provides live job posting data from over 49,000 sources that can be queried by SOC codes, locations, names of employers, certification requirements, skill requirements, job titles, education level requirements, education programs, and/or job types. Online ads are retrieved from a variety of sites, including job boards, job aggregators, and individual companies. The RTI data set is updated daily. RTI are deduplicated, also known as counts of "unique" ads; that is, before being brought into the RTI data set, all ads are compared against each other, and duplicates are removed.
[3] https://news.crunchbase.com/startups/tech-layoffs/
Job Postings and the Stock Market Diverge as Generative AI Becomes Mainstream
Since the introduction of ChatGPT, the impact of generative AI on the labor market can be seen directly in job postings. Since October 2022, one month before the release of ChatGPT, job postings declined 25% while the S&P 500 increased 53%. This relationship is not only driven by the largest companies. The S&P 500 equal weight index also increased during this time, as did mid-caps and small caps (although small caps only increased about 7%).
Hiring also fell during this period, albeit to a lesser extent than job postings. Hires from the Bureau of Labor Statistics JOLTS survey declined almost 10% as the S&P 500 increased over 50%.
Tech Sector Stocks Surge as Job Postings Plunge
The inverse relationship between market performance and job postings is particularly pronounced for the tech sector. The S&P 500 Information Technology (IT) sector soared more than 100% since October 2022 on investor excitement about artificial intelligence. During 2023, the “Magnificent 7,” [4] a group of tech stocks that all either make use of AI or enable the adoption of AI, led the stock market, and stocks continued to rise through 2024. In contrast, job postings for computer occupations, including software developers, programmers, and database architects, have declined 53% since October 2022.
Source: S&P, JobsEQ® by Chmura
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[4] This group includes Apple, Amazon, Microsoft, Alphabet, Meta, Tesla, and Nvidia.
Continued improvements in generative AI and agentic coding tools can result in leaner teams with fewer junior employees, rendering computer occupations particularly susceptible to generative AI. Additionally, computer-related occupations account for higher-than-average labor costs, with a mean annual wage of $118,000 compared to $68,000 for all occupations in the United States. Software developers account for the largest portion of computer occupations and have a mean annual wage of $145,000.
This trend, however, is not limited to the IT sector but generalized across the entire economy. The S&P 500 excluding IT began to diverge from job postings excluding computer occupations during a period when generative AI became more established as an enterprise tool. Since October 2022, the S&P 500 excluding IT has increased 37%, but job postings excluding computer occupations have decreased 23%.
Financial occupations[5] also demonstrate susceptibility to generative AI. Many of the administrative and pattern recognition-based tasks associated with occupations in finance have the potential for automation. Financial occupations are also well paid, with an average annual salary of $107,400. Despite the ability to apply AI in financial occupations, a much weaker relationship exists between financial occupations and the S&P 500 finance sector than exists in the relationship between computer occupations and the S&P 500 IT sector. Job postings for financial occupations have declined 24% since October 2022, while the S&P 500 finance sector has increased 50%. This 74-percentage point spread is dwarfed by the 155-percentage point spread between computer occupations and the S&P 500 IT sector.
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[5] Financial occupations are defined by occupations in which over 25% of employees work in the finance and insurance sector.
Shift, Bubble, or Both?
Two factors likely impact the relationship between job postings and the S&P 500.
First, creative destruction is occurring. Labor markets adjust with new technological changes. Enhanced productivity reduces the number of hours to complete a task and may even lead to a reduction in the number of workers needed. Since job postings and hirings both declined while the stock market rose, the labor market is likely shifting in response to the entrance of generative AI. Even firms and occupations less associated with generative AI have diverged since October 2022, suggesting a widespread shift. It remains unclear how and to what extent labor markets will continue to adjust to generative AI.
Second, the wide gap between the soaring S&P 500 and plunging job postings for computer occupations suggests there may be a bubble in the AI investment space. When compared to the spread between the S&P 500 finance sector and job postings for financial occupations, this becomes clearer. Despite financial occupation tasks possessing similar potential for automation as computer occupation tasks, the finance sector has not experienced as high of stock price payoffs for lower hiring as the IT sector. This suggests that the firms and investors in the IT sector may be overestimating the labor-cost saving potential of generative AI.
The generative AI bubble shares characteristics with the dotcom bubble of the late 1990s, which led to a crash in the Nasdaq in 2000 and a recession in 2001. Like the internet of the 1990s, generative AI is a widely publicized new technology that has caused investor exuberance. Like the dotcom firms of the 1990s, generative AI firms are backed by abundant capital, but they are generally not yet profitable, and leaders are questioning when and to what extent we will see returns on investment for AI.[6] There are also more prominent voices raising concerns that, while still useful, the reasoning abilities of generative artificial AI may be exaggerated.[7] Similarly, generative AI may have a lower impact on economic growth than its proponents suggest.[8]
Questions remain about whether AI investment will continue to put upward pressure on stocks. While it was a major driver of the market, other variables now play impactful roles. In 2025, policy uncertainty has taken precedence over AI developments, and investors continued to debate when and how aggressively the Federal Reserve will cut rates. The uncertainty that characterized 2025 has led to stagnating labor turnover in a low hiring and low firing environment as firms await policy developments. As stressors emerge in the economy and market, we will see the extent to which generative AI’s potential is met or if the AI associated bubble will burst.
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[6] https://www.ibm.com/downloads/documents/us-en/12f5a711174dc2ac
[7] https://ml-site.cdn-apple.com/papers/the-illusion-of-thinking.pdf
[8] https://academic.oup.com/economicpolicy/article/40/121/13/7728473