Economy-wide breakdown
- The fourth quarter of 2024 fueled hopes for strong labor market growth in the new year. While October’s jobs report fell significantly below expectations due to the impact of Hurricane Milton, November and December exceeded forecasts. Over the past three months the job market has grown at a respectable average of 170,000 jobs—an encouraging sign given the backdrop of still-high interest rates.
- While overall job growth remains steady, the labor market is a far cry from the peaks in the early 2020s, which led to the “Great Resignation”. Now, fewer workers are quitting their jobs, leading to fewer backfill openings and ultimately driving down the hiring rate. Despite this slowdown in quitting and hiring, layoffs have not risen significantly, creating a relatively stable environment for those currently employed.
- For workers with jobs, this means consistent wage growth and a moderate selection of open positions to explore. However, the picture is less optimistic for unemployed workers. The labor market has become increasingly challenging, with the job-finding rate—the percentage of unemployed workers securing jobs each month—declining steadily over the past six months.
- As we look ahead to 2025, steady labor market growth is expected to continue. However, policy uncertainty under a new administration will be a critical factor in shaping the trajectory of the labor market. Decisions on fiscal and monetary policy, as well as regulatory changes, could significantly influence hiring, wages, and overall economic momentum in the year ahead.
Read our economy-wide breakdown of the latest numbers.
Employment Trends
Many in the tech industry will be eager to leave 2024 behind, a year defined by layoffs and a decline in job openings. So, what does 2025 hold? This year, ChatGPT’s public availability reaches its three-year milestone, reflecting a period when generative AI has shifted the priorities of major tech companies. These firms are now channeling significant investments into the hardware and software needed to develop enterprise AI models.
Just three days ago, the Stargate Project was announced—a groundbreaking collaboration between OpenAI, SoftBank, Microsoft, NVIDIA, and others, committing over $500 billion to AI advancements over the next four years. This is just the latest example of impressive investments in AI and nowhere is this AI-driven shift more visible than in the surge of data center construction. Annual spending on these facilities has surpassed $30 billion, tripling in just two years. These massive computing warehouses form the backbone of tech giants’ efforts to fulfill the promises of enterprise AI.
Has this frenzy translated into hiring demand for tech workers? Not quite yet. Employment growth in 2024 was minimal at best and slightly negative at worst. By the end of the year, the information industry—the BLS category encompassing many tech jobs—averaged a modest net gain of 4,000 jobs over a three-month period. During the summer, the picture was even bleaker, as the industry lost nearly 10,000 jobs a month on average. The good news is that hiring demand began to rebound toward the end of the year, with steady growth since October offering a glimmer of hope for 2025.
Within the tech job subsectors, engineering and research and development are leading growth, expanding at rates of 4.3% and 1.1%, respectively. In contrast, the sharpest declines in hiring demand are seen in software publishing and management consulting. Both industries, which were growing at rates exceeding 10% just a few years ago, have slowed significantly to 1.6% and 0.5% growth, respectively.
Wage Trends
As hiring demand has slowed, so too has wage growth for tech workers. All subsectors have experienced a decline, with the sharpest drops occurring in scientific research and management consulting, where wage growth is now at 2.6% and contracting at -0.1%, respectively. Meanwhile, wages for engineering and software publishing have also cooled but remain comparatively stronger at 5.7% and 4.3%.
Openings and Turnover Trends
Total job openings in the tech sector remain well below their peak of 8%, now sitting at 4.8% following a period of volatility. One of the most concerning trends is the rise in the layoffs rate, which has climbed above 1.4%, thus surpassing pre-pandemic levels. With fewer job opportunities and increased layoff risks, job seekers are quitting at just 1.1%, the lowest rate since 2013. This combination of higher layoffs and lower quits has driven the hiring rate down to 2.6%, reflecting reduced demand to backfill positions.
Recruitment Marketing Trends
The term “long” or “ATS apply” refers to the conventional application process, requiring applicants to manually submit their tailored application documents and personal details through the company’s website or an applicant tracking system (ATS). In many cases, applicants are required to create a company-specific account.
On the other hand, “easy apply” refers to a swift application process on a job board, often conducted through a smartphone. With a single click, essential information like the resume is transmitted directly to the company. Due to the simplicity of this application method, easy-apply metrics are not directly comparable to those of the “long” or ATS apply. The metrics are therefore presented separately.
Long Apply
As employment demand declined and layoffs increased in the tech sector, recruiting costs have dropped while conversion rates for open roles have improved. The median cost-per-click for science and technology jobs recently edged past $1. Similarly, cost-per-application saw a brief year-end surge, reaching over $20 for technology roles and $15 for science, but the overall trend holds steady—recruiting costs for tech workers remain well below their peak. This is largely due to higher application completion rates, with apply rates nearing a record 7% for both categories, indicating increased engagement from job seekers.
Easy Apply
Short or easy apply recruiting costs are following a similar downward trend as traditional application methods. Cost-per-clicks (CPCs) have hovered around the $1 mark for most of the year. Cost-per-application (CPA) has shown a slight increase for science jobs, reaching $9, while continuing to decline for tech jobs, now just under $4. These trends are driven by steadily improving conversion rates, which have risen to 13% for science roles and 21.5% for tech workers, continuing to prove an effective channel to attract job seekers.
Recruitment Marketing Forecasts in Technology
While 2024 was a challenging year overall, the surge in investment in artificial intelligence could lead to increased competition for skilled software engineers and research scientists. Our cost-per-application (CPA) forecast suggests that recruiting costs will remain mostly stable over the next two quarters, despite this potential uptick in demand for top talent.
What does this mean for technology?
The tech sector stumbled through 2024, grappling with layoffs, declining wage growth, and uneven job openings. Yet, a shift is underway. The $500 billion Stargate Project and surging data center investments signal that artificial intelligence could be the industry’s next growth engine, creating new demand for engineering and research talent.
While hiring demand hasn’t fully rebounded, application rates have hit record highs, and recruiting costs remain far below their pandemic-era peaks. With conversion rates rising across both traditional and easy apply methods, recruiters are well-positioned to attract top talent as competition heats up in AI-driven fields. Looking to 2025, the question isn’t whether the demand for skilled workers will rise—it’s how fast the labor market will respond to the next wave of innovation.
Forecasting Methodology
Cost-per-application (CPA) is forecasted two quarters ahead using the previous two years’ worth of one-month moving average data. A combination of ARIMA, exponential smoothing, and seasonal naïve models are used to create an ensemble forecast. The forecast provides both the 95th percentile confidence intervals, indicating the likelihood that each value will be within the CPA range provided.
