Business
Companies are overhauling their hiring processes to screen candidates for AI skills—and attitudes
As companies race to incorporate AI into their workflows, it’s not only models and tools they’re relying on for a competitive advantage but, increasingly, people. Across industries, 66% of business leaders said they would not hire someone without AI skills, according to the 2024 Work Trend Index Annual Report by Microsoft and LinkedIn.
Company leaders and professionals in the hiring space say they’re now specifically considering candidates’ proficiency with AI tools and sometimes even prioritizing these skills over professional experience. They’re also reimagining their hiring processes, developing new ways to screen for candidates’ familiarity with and ability to use AI tools. Their approaches range from focusing interview conversations on AI—providing an opportunity to gauge a person’s familiarity with and attitude toward the technology—to having candidates complete tasks with AI tools and observing how they use them.
“Every organization is—no matter what the skill set might be—looking to see if they can find someone that potentially has some experience with AI, and specifically generative AI, and now you’ve got agentic AI on the horizon, so they’re definitely looking for people who have experience in those areas,” said Thomas Vick, senior regional director for technology at talent and consulting firm Robert Half.
Skills take center stage
Vick said he noticed the emphasis on AI skills in hiring emerge about a year ago and continue to accelerate ever since. The clear trend is that AI skills are now deemed as important as experience and education.
In the LinkedIn and Microsoft report, which included insights from a survey of 31,000 people from 31 countries, 71% said they would hire a less experienced candidate with AI skills over a more experienced candidate without them. PwC’s 2024 AI Jobs Barometer states that skills sought by employers are changing at a 25% higher rate in occupations most able to use AI, such as developers, statisticians, and judges. Additionally, a study on hiring trends in the U.K. found that candidates with AI skills are landing wages 23% higher compared to those without, making a greater difference than higher degrees up until the PhD level.
Alyssa Cook, a senior managing consultant at hiring and staffing firm Beacon Hill, has also observed that hiring teams are more willing to hire candidates with AI skills. What’s more, she said, skills with specific AI tools a company is using or wants to adopt can even take precedence over an overall greater depth of experience with AI.
“Companies would rather hire a candidate who has hands-on experience with a particular tool they are implementing if they have the ability and interest to train up on other skills,” she said
The newfound focus on AI skills in hiring is happening across the various departments of companies. Vick said he’s seen it across accounting, finance, creative roles, and especially technical roles. According to job listing data cited by the Wall Street Journal, one in four U.S. tech jobs posted so far this year are looking for people with AI skills.
The AI test
Automation firm Caddi is one company where this is playing out across the organization. CEO Alejandro Castellano said interviewers regularly ask candidates about their experience using AI tools; for technical candidates, the firm encourages individuals to use AI coding assistants like Cursor, Claude Code, or Copilot during code analysis and technical exercises.
“We want to see how they work in real conditions,” said Castellano.
The approach flips on its head the way companies have traditionally tested candidates for software engineering jobs. Typically, coding tests have been designed to isolate candidates from their real workflows in order to assess their fundamental knowledge. In a world where AI tools are increasingly used to help employees accomplish particular tasks, however, this old approach hardly makes sense. In their day-to-day duties, developers and engineers must be able to work effectively with these systems to enhance their own productivity—not delve into the realm of theory and concepts.
“We’re moving toward exercises that reflect how engineers actually work, how they search, use AI suggestions, and debug. We care as much about how they solve a problem as we do about the end result,” Castellano said.
Ehsan Mokhtari, CTO of ChargeLab, a company that creates software for electric-vehicle charging, said encouraging candidates to use AI tools has become a formal part of the firm’s hiring process. The effort started a year ago after it was noticed that candidates were avoiding using AI tools, assuming they would be penalized for it. So the company revamped its hiring process and its broader operations to embrace AI tools, starting with restructuring take-home challenges for technical candidates and then rolling out the effort for positions across the company.
“We started with engineering, but we’re now pushing it org-wide. Sales came next—they were surprisingly fast to adopt AI. Tools like ChatGPT are now common for them for research and outbound comms. We’ve made AI literacy part of departmental OKRs,” Mokhtari said. “That means every function—support, product, sales, engineering, operations—is expected to include it in their hiring considerations.”
In working with clients on their hiring, Robert Half’s Vick has seen a variety of approaches to screen candidates for AI skills. Some companies are turning to their contractors, Vick says, asking those with AI experience to help them evaluate candidates during the interview process. One of the most popular techniques he’s seen is bringing job candidates into a “sandbox” environment and having them actually show how they would utilize AI within that environment to complete various tasks. It’s the same idea as the reimagined coding assessments, but applicable to any role in the organization.
Attitude goes a long way
While company leaders generally say they would hire a candidate who is proficient with AI over one who isn’t, they also stress that there’s more to it than skills: Attitude also plays a significant role.
ChargeLab’s Mokhtari explained that he looks at AI proficiency in two layers: skill set and mindset. While skill set is highly desirable, it can also be easily taught. Mindset, however—being proactive in using AI, curious about where it can add value, and not being combative toward it—“is harder to coach and more important long-term,” he said.
Castellano echoes this idea. He’s found that understanding how someone thinks about and works with AI is one of the strongest signals the company has found to gauge that person’s ability to keep delivering value in a fast-changing environment.
“We’re not just looking for people who know the tools,” he said. “We’re looking for those who are curious, adaptable, and thoughtful about how they use AI. That mindset makes the biggest difference.”
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