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ZDNET’s key takeaways
- Seventy-three percent of tech job ads require AI skills.
- Job seekers need to demonstrate their AI fluency.
- Domain expertise remains crucial.
More job descriptions than ever are soliciting AI skills, according to a new report from tech hiring platform Dice.
An analysis of 7 million tech job postings in the US from May 2026 revealed that 73% required at least one AI skill, underscoring that a practical grasp of the technology is becoming a baseline expectation among employers. In January 2024, that percentage stood at 15%.
“A lot of these [skills] are going to just become table stakes,” Dice CEO Art Zeile told ZDNET.
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For tech job seekers already navigating a rocky job market, proving to employers that they have the necessary skills is paramount.
How much do certifications matter?
Though the tech job landscape is rapidly shifting, there are some tried-and-true practices that can help prospective hires communicate to employers that they can actually do the job.
One, Zeile said, is certifications.
Certifications have long been a way for IT professionals to demonstrate proficiency in various areas. Zeile said Dice has been tracking the emergence of certifications for AI skills. Two years ago, job seekers might not have had many options. Now, companies like AWS and Google offer certifications for generative AI developer, machine learning engineer and more.
“If you ask me, what would be super impressive… you went through a training program, and you passed the test. You’re certified,” Zeile said.
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Zeile also spoke to the importance of being able to talk through projects and their results.
Columbia University’s Center for Career Education, for example, advises not just listing generic job duties on a resume, but what you accomplished, how, and why.
Saying you know Python isn’t enough. Pointing to a project that perhaps saved your last company time or money is a different story. Zeile said that could also mean coming into an interview with an agent you’ve built.
Additionally, the Dice report called out the importance of the intersection between a candidate’s own area of expertise and their fluency with AI tools.
Dan Hillman is an interview engineer at Karat, a company that runs technical assessments for clients such as Google, Goldman Sachs, Mastercard, and others. He said he’s looking for how well candidates can use their own expertise to audit and manage AI tools to solve a problem, rather than just deferring to the AI.
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“[It’s] not about testing only how well you can work with AI. It’s testing how well you work in your domain, augmented by AI,” he said.
Hillman recommended doing practice problems ahead of the interview, using AI. Find a problem, come up with your own approach first, and then work with the AI tool, and always go back and review.
“That is how you can exercise your muscle while ensuring that you have that AI proficiency skill,” he said.
Personal plans for continued reskilling
He also emphasized the importance of explaining your process — how you gather information up front, write specific prompts, question outputs, and budget time.
Apart from a technical interview, candidates can also demonstrate their proficiency by talking through their personal plans for continued reskilling, said Michael Morris, global head of platform and talent at Randstad Digital.
“Job seekers today that don’t come in with a real training and upskilling personal plan — I wouldn’t consider them,” Morris said, noting that resources like online courses can help tech professionals stay nimble, especially as new models crop up so quickly. Candidates have to show that they have a strategy to keep up.
Further, Morris said it’s important for candidates to understand how their job role might be affected by advances in AI and show they have a plan, particularly if their specialty is vulnerable to displacement.
