Despite lingering economic fears, the tech unemployment rate hit 2.1 percent in October, according to new U.S. Bureau of Labor Statistics (BLS) data analyzed by CompTIA.
That’s the slightest of declines from September, when the rate stood at 2.2 percent, and matches August’s rate. It’s also significantly lower than the national unemployment rate of 3.9 percent.
“Fair to say tech employment gains for the month exceeded expectations given the recent labor market swings,” Tim Herbert, chief research officer at CompTIA, wrote in a statement accompanying the data. “Companies continue to focus on the technologies and skills that deliver meaningful business value.”
Companies within the tech industry added an estimated 2,159 workers last month, while tech occupations across the broader economy increased by roughly 483,000 jobs. Collectively, employers posted around 167,000 job postings for the month, contributing significantly to the 2.2 million postings through 2023 so far. In other words, tech hiring remains robust, with employers hungry for tech professionals with a variety of skills.
But which skills? According to CompTIA, some of the roles in greatest demand include software developers, IT support specialists, systems analysts and data scientists. There’s also a notable rise in the number of artificial intelligence (A.I.) positions; keep in mind, however, that despite the hype, the overall number of A.I.-intensive jobs remains relatively tiny for the time being.
According to a recent Dice.com analysis, all industries are hiring A.I. talent, with education and real estate taking some of the biggest leaps in job postings over the past few years. Healthcare and information have also enjoyed a sustained burst of A.I.-related hiring, despite the numbers declining recently.
Want to apply for an A.I.-related job? It’s worth reading a new report from consulting firm McKinsey, Technology Trends Outlook 2023, that highlights the underlying concepts anyone interested in A.I. should learn:
- Machine learning
- Computer vision
- Natural-language processing
- Deep reinforcement learning
On a tactical level, that might mean an A.I. specialist will engage in everything from training models to figuring out the hardware needed to power these intensive processes. Even if your job doesn’t currently involve A.I., stay aware of the technology’s progression, because chances are good that A.I.-powered tooling will find its way into your workflow at some point.
