Today’s workforce is rapidly changing, along with the tools and technologies used to perform work across all industries. With the rise of AI and similar technologies, more employees – and companies – are attempting to set themselves apart by focusing on their unique skills, rather than just checking off boxes on a list. In the competitive IT and cybersecurity world, where specificity of skills matter immensely, how can employers ensure they’re finding the best-fit people for critical roles – and could AI actually help?


An Emphasis on Skills Is Trending

In a 2023 survey by PwC, 35% of employees say they have skills that aren’t clear from their qualifications, job history or job titles, while 27% say that their employers focus too much on job histories and not enough on skills. A skills-first talent strategy, in contrast, allows recruiters to identify candidates with the real-world, practical abilities necessary to excel in a given role.

This approach is particularly valuable in executive positions where specific skills, such as strategic thinking, leadership, and problem-solving, are critical for success. Similarly, it’s a serious consideration for highly technical roles, where particular certifications and/or specialized skills are not just preferred, but absolutely required.

This shift towards skills also means a shift away from another traditional marker of qualification: degrees. Research conducted by the Harvard Business Review and labor-market data company Emsi Burning Glass found that, between 2017 and 2019, employers reduced degree requirements for 46% of middle-skill positions and 31% of high-skill positions, and IT was one of the most-affected fields. Their research did find, however, that tech companies have differed wildly in their de-prioritization of degrees: by the end of 2021, only 43% of IT job listings at Accenture and 29% at IBM required degrees, but more than 70% of those at Apple and Google did so.

The increased emphasis on skills highlights the increasing diversity and priorities of the tech talent pool. Reducing degree requirements may open the door to more non-traditional talent who, perhaps, didn’t take a “standard” path but do have exceptional skills that make them a good fit. It can even help remove barriers to these jobs for those who have traditionally been less-represented in these fields. The key is to ensure that candidates have both the “hard” technical skills and the “soft” social and collaborative skills necessary to succeed.


How to Implement Skills-First Hiring

While every talent strategy will look a little different, a few key actions can reap great dividends for your company. These include:

  • Identify the key skills for each role. Start with the basics: which skills are essential for a given position? Is it a business-oriented leadership role? A high-level technology exec? These skills should include both specific abilities and/or certifications (hard skills) and interpersonal and emotional intelligence (soft skills).
  • Utilize skills assessments and structured interviews. Skills assessments can become part of the hiring process, tailored to the specifics of the role. This might include practical tasks, simulations, or problem-solving exercises. Similarly, structured interviews can target candidates’ skills to ensure a thorough – and fair – evaluation.
  • Invest in upskilling and career development. As noted by the Harvard Business Review, companies across the board have been investing millions of dollars into “future proofing” their teams with upskilling, continuing education, and other support for career development. Building a reliable and loyal internal pipeline – which also focuses on skills-based training – is every bit as important as developing a skills-centric strategy for external hiring.

Perhaps most intriguing is how AI could play a role in driving these skills-based hiring strategies. Strategy + Business recently spoke with Shay David, the CEO of, an AI platform focused on talent management and development, about how his company’s tools are designed to identify skills (and skills gaps).

“It’s able to scan many different information sources, such as job boards or LinkedIn. And then, it’s using an AI technology called NLP (natural-language processing) to be able to understand text—plain English text or plain Hebrew text or any other language—and to be able to capture the skills information from that. So, in essence, we developed two main technologies. One is a big knowledge graph that understands the relationship between roles and tasks and skills. And the second is a language engine that is able to take normal text and be able to map that into that graph. Once you have both of those components, then you can ask a lot of questions about the data and understand it in a dramatically more granular and actionable way.”

The resulting technology allows for AI-powered, large-scale data analysis to capture and apply knowledge about necessary skills in a way that drives successful recruiting. Rather than replacing human work, this application of AI is all about helping people maximize their potential and helping companies pinpoint how best to utilize employees’ skills. It’s a hopeful outlook. As David puts it, “The solution in our minds is to help [people] tap into the same skills platforms so that they can understand what are the skills that are 21st-century skills, and how they could find training pathways that are going to give them the path back to full employability.”

By Daniel Midoneck