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Two-thirds of business leaders say they wouldn’t hire someone without AI skills, and an even greater share say they would rather hire a less experienced candidate with those skills than a more experienced candidate without them, according to a recent Microsoft and LinkedIn report.

Ever since we saw that stat, we've wondered: What exactly are “AI skills”?

Microsoft and LinkedIn’s report defined such skills as the ability to use genAI tools such as ChatGPT or Copilot. That’s a fine starting point, but beyond that, what are essential AI skills and how do you identify them in job candidates and develop them in yourself and non-technical colleagues?

We posed that question to several leaders and here’s what they told us:

1. An understanding of the basics of AI.

Many companies that have launched AI training programs emphasize general AI literacy. Consulting firm Booz Allen Hamilton, for example, offers an optional “AI Aware” course, half of which covers basic concepts like machine learning and deep learning, explains Yvette Wolfe, who designs much of the firm’s data and AI training curriculum. The other half of the course focuses on AI knowledge that’s specific to Booz Allen Hamilton, like the firm’s approach to selling AI and how the company identifies the AI needs of its federal clients. Employees who want to go further in depth can take the company’s “AI Foundational” course, which builds off those concepts.

Kian Katanforoosh, CEO of skills-intelligence platform Workera, explains that some of the more popular AI assessments for non-technical individuals on his company’s platform fall under the umbrella of “AI fluency,” which includes domains like “communicating about AI” and “generative AI.” The latter assesses an individual’s knowledge of how genAI works, their ability to identify appropriate applications of the technology, and their knowledge of the ethical questions surrounding the technology, among other things.

2. The ability to use AI in your work.

Arguably even more important is that employees know how to use genAI in their jobs. This can mean a lot of different things depending on an employee’s role. If you’re a marketer, you might use it to draft marketing copy. If you’re in human resources, you might use it to analyze the results of the latest employee pulse survey. This set of skills is “more tied to the tasks that [an employee has] on the job,” says Katanforoosh.

One broadly applicable skill is often referred to as “prompt engineering,” which is essentially the ability to get genAI tools such as ChatGPT to produce good results. We question whether “prompt engineer” is a job title that will be around forever, but eliciting useful answers from AI—as Google searching is already—will be an important skill for many people’s jobs.

A question to ask yourself and others: “How are you creating the prompts that actually get you the answers that are going to effectively move your work forward?” says Alana Brandes, chief people officer of education and upskilling company Guild. She gives the example of one of the company’s recruiters who built a GPT, a tailored version of ChatGPT, that has saved their team time by creating behavioral and skills-based questions for candidate interviews.

Using genAI effectively in one’s job also hinges on understanding its capabilities and limitations. The capabilities side includes knowing all of the tasks in your job that a tool like ChatGPT or Claude can help you with. The limitations side includes knowing where a model is likely to make an error or lead you in the wrong direction.

We know from research on BCG consultants using genAI that it’s not always obvious where the technology is going to improve performance or worsen performance. (The researchers call this a “jagged frontier,” since the boundaries aren’t intuitive.) Knowing AI’s capabilities and limitations is an important skill that develops over time. “After 10 hours [of using it], you're sort of like, ‘Oh yeah, this is going to work. This is not going to work,’” Ethan Mollick, an associate professor at Wharton and one of the authors of the jagged-frontier paper, told us earlier this year.

3. Other skills that matter more with AI.

While developing AI-specific capabilities is important, leaders told us they’re also prioritizing other skills that complement working with the technology. One of the biggest ones is critical thinking. “In a world where there's more fake data generated, there are more assistive technologies, it is even more important to be critical of what you see,” explains Workera’s Katanforoosh. In the BCG study mentioned above, for example, consultants using AI were, on average, 19 percentage points less likely to land on a correct solution for one of the tasks than consultants not using AI. That wasn’t just the AI’s fault—the consultants who performed poorly with AI “tended to blindly adopt its output and interrogate it less,” in the words of the researchers.

In his book Futureproof, the New York Times’ Kevin Roose points to the importance of what he calls “machine-age humanities.” The skills he argues are essential for the future include the ability to remain focused amid distraction, to rest and stave off burnout, and to anticipate future consequences of technology.

Underlying all the AI and complementary skills is something many leaders see as increasingly crucial in a world with AI: the capacity to learn and adapt. Learning agility—the ability to continuously acquire new skills as technology evolves—is one of the more popular skills leaders are prioritizing. Brandes emphasizes the importance of a willingness to experiment and engage with something that feels uncomfortable or outside of one’s core expertise. This is an “important skill as it relates to AI that you might not think of on its face,” explains Brandes, “but it's probably the biggest barrier to entry for many.”

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Steal this idea

Workera’s Katanforoosh told us there’s a section of the company’s interviewing process where he or one of his colleagues ask candidates how they’ve used AI in their daily life. Once they get an answer, they dig deeper with questions like, “What have you encountered as a challenge?” and “What would you do differently now?” These types of questions give them a sense of how much experience candidates have using AI and what their skill level is.

©2024, Charter Works, Inc. This article is reprinted with permission from Charter Works, Inc. All rights reserved.