This post was originally published on this site.
The tech unemployment rate ticked upward last month, hitting 3.4 percent, according to the latest U.S. Bureau of Labor Statistics (BLS) data analyzed by research firm CompTIA. That’s still notably below the national unemployment rate of 4.2 percent.
Once you dig into the data, a more nuanced picture emerges. For example, the tech services and custom software development subindustries added some 3,400 workers in August, even as tech manufacturing lost 2,500 workers. Job postings for tech positions increased to just over 500,000 last month, while actual tech occupation employment declined by 28,000 positions.
“The bumpy stretch of tech labor market data requires the usual balancing of shorter-term and longer-term perspectives,” Tim Herbert, chief research officer for CompTIA, wrote in a statement accompanying the data. (Or as Charles Dickens once said: it was the best and worst of times.)
Employers remain hungry for tech professionals regardless of their formal degrees. “Job posting data suggests that many employers remain focused on skills-based hiring and considering candidates who traveled alternate pathways to the workforce,” added CompTIA’s report. “In August, 45 percent of active tech job postings did not specify a four-year degree requirement among candidates. Several key occupations recorded even higher percentages, including network support specialists (86 percent), IT support specialists (72 percent), network and systems administrators (51 percent), web and UI/EX designers (48 percent) and database administrators (47 percent).”
For those currently hunting for a job, specializing in “hot” skillsets such as AI can make you stand out in a crowded and often uncertain market. On Dice’s ‘Tech Connects’ podcast, we recently hosted Seth Robinson, who’s vice president of industry research at CompTIA, to talk about the impact of AI on the current hiring market:
For anyone who’s in the market for tech talent, especially in an AI context, it’s important to remember that a lot of planning needs to go into any kind of AI implementation, starting with ensuring your data is cleaned, organized, and ready for use. From there, it’s critical for companies to evaluate what they want out of AI, whether they have the budget to drive those results, and whether they can effectively adopt a holistic approach (i.e., teams working in sync to accomplish an AI strategy). After that, you’ll have a better idea of what you actually need when it comes to AI-related talent.