How to Accelerate Skills-First Hiring in the Age of AI

Talent is distributed equally. Opportunity is not. That’s why skills-first hiring is so imperative, giving talent professionals a chance to look at all of a candidate’s skills and experiences, not just their pedigree.

And now along comes AI, which has the potential to turbocharge skills-first hiring. 

“Before AI, we saw skills as a better way to match talent and opportunity,” said Aneesh Raman, vice president at LinkedIn and head of the company’s Opportunity Project. “But we often dealt with fixed systems, fixed playbooks, and a lot of biases about how to manage talent.” 

Aneesh shared this perspective recently as the moderator of a Talent Connect panel on Accelerating a Skills-First Future of Work in the Age of AI. AI, he noted, could create a new playbook for developing talent and technology. To unpack this possibility, Aneesh chatted with three skills-first experts: Cat Ward, vice president at Jobs for the Future; Gerald Chertavian, CEO of Year Up; and Byron Auguste, CEO of Opportunity@Work. Here’s what they had to say. 

1. Focus on your intention when using AI  

For all the hype surrounding AI, the panelists agreed, it’s simply a tool. “Technology is a tool,” Byron said, “just like a hammer is a tool. You can use a hammer to build a house. Or you can use it to smash someone’s head, right? What matters is your intention.” 

Byron explained that if “the systems your AI is landing in” already overlook candidates who don’t have bachelor’s degrees, you’re “paying to be blind to more than half the population’s skill sets.” Byron knows how talented this group can be; Opportunity@Work champions expanding opportunity for STARs, people who are “Skilled Through Alternative Routes.” 

But if you use AI to find more sophisticated ways to screen people in — rather than screening them out — and to sort through complex data that can help you pick the right person for the job, he said, then “AI is incredibly powerful.” 

Byron said that AI can help recruiters by identifying the “skills proximity between where someone is and where they need to be for a job.” A candidate, for example, may currently be in a role where they’re making considerably less money than the role you have available, but their skills gap is relatively small. “And if you can identify that precisely,” he said, “you can develop the human capital. You can match it, and it’s a very powerful unlock.” 

2. Be thoughtful about the objectives you put into your AI technology

Gerald compared AI to a GPS system. After you plug in an address, it’s likely to guide you along the fastest route. But if you’d rather take a scenic route, with stops along the way, you need to plug that information in. He added that blindly following a GPS could also lead you down a closed road or unsafe terrain.

Likewise with AI. “We’ve got to be thoughtful as to what objectives we’re giving the tool,” Gerald said. “We have to keep our hands on the wheel and our eyes on the road because we are the ones in charge.” 

This is especially important to him because Year Up is helping over 40,000 young adults without four-year degrees access careers with livable wages — not always easy, in the face of potentially biased AI algorithms. 

One of the most important objectives your AI could achieve, Gerald said, is helping people gain new skills once they’re already in a job. It usually falls on managers to help employees develop skills. But many managers are so overworked, they don’t get around to it. 

“AI could help you [the employee] more clearly see the skills you have and provide the gap analysis you need to gain those skills within your organization,” he said. “I think the role of manager will change because of this too.”

By making the skills paths more transparent, Gerald said, AI “will do more to push the skills-first movement forward than anything else we’ve ever seen.” 

3. Use AI to create a common language for your skills taxonomy 

One of the biggest challenges companies face as they transition to skills-first is developing a skills taxonomy. Organizations don’t always know what language to use to identify different skills or even which skills to include. That’s where AI can offer a big lift, Cat said.

Her organization, Jobs for the Future, focuses on helping people who face systemic barriers get high-quality jobs. The nonprofit works with policymakers, educators, and companies — and most organizations, she says, are still in the early stages of moving to skills-first. To get going, she urges them to start with the “big hot jobs they’re trying to hire for right now.” 

Once they’ve done that, she urges organizations to quickly develop a taxonomy — one that speaks a common language throughout the talent management system and makes sense to those outside the business. 

“What’s the taxonomy that makes sense with other employers?” Cat asked. “And that works for community colleges, the HBCUs, or if you want to tap into the STARs profile?” Your taxonomy, she said, is the foundation “that is going to allow all of us to speak a common language.” 

What’s more, AI can play a crucial role in creating that language. “AI,” she added, “will help us work better and with greater fluency across an entire ecosystem of players.” 

Final thoughts: “A better world of work at the other end” 

If there’s one thing everyone on the panel emphasized, it was hope. “If we can get the intent right, get the systems right, get the playbooks right,” Aneesh told the audience, “there is a better world of work at the other end.”

Aneesh said that a world in which opportunities would be available to everyone could even be realized within the panelists’ lifetimes. “We’ve been at this skills-first movement for some time and that is our north star,” he said. “AI has accelerated a lot of it. But it all centers on intent.”