​As our latest Global Talent Shortage report demonstrates, the skills gap affecting the vast majority of employers and industries is very real and durable.

While some of the shortage is due simply to demographic, technological, and macroeconomic factors, talent acquisition leaders must actively seek to change a system that no longer works as it once did. Necessity is the mother of invention, and now is the time to set aside established patterns and processes. Embracing new ways of thinking will enable employers to forge ahead with generative artificial intelligence (AI), the emerging green economy—and whatever other breakthroughs are around the corner.

With that, here are some obvious recommendations to consider:

• Stop! It’s an old joke: A person complains to their doctor about the sharp pain they experience when they hit their thumb with a hammer. “So, stop doing that,” the doctor advises. When it comes to talent, then, those who complain about their inability to find it may benefit from stopping to look for it in the same old places. For example, stop insisting on the same universities, the same degrees, the same old hard skills and qualifications. It isn’t working. There aren’t enough candidates that check all those boxes, and the competition for those who do is absolutely bloodthirsty. If you are trying to find a date by always visiting the same bar, at some point you need to realize that it’s time to go somewhere else, and a new strategy should always start with the abandonment of the old, obsolete strategy.
  
  Already today, and especially tomorrow, what you know is less important than what you are able to learn. We’re all reimagining our jobs on the fly due to artificial intelligence and other innovations. Recruitment must reflect this new reality, hiring on present and future potential for tomorrow’s roles, rather than past performance or talent for yesterday.

• Upgrade your mindset. This is, of course, the corollary; once you take the brave step of rejecting the old ways, you make room for new approaches. You are able to focus on potential, on the future. What soft skills will candidates need in order to succeed? What departments and industries are they working in now that, while not an obvious fit, might help fill the skills gap?
  
  One example of this skills adjacency can be found in the world of computer gaming, where we have found that nearly two-thirds of employers plan to consider gaming skills in future hiring, and no wonder: creativity, critical thinking, problem-solving, leadership, and collaboration can all be demonstrated, and to some degree harnessed, in the rich and challenging universe of games. Combine these soft skills with gamers’ obvious comfort with technology, and you’ve got a huge and heretofore overlooked talent pool.
  
  Another increasingly important, though usually neglected, factor is a candidate’s value system. We know that younger workers, more than their older counterparts, like to feel their employer has a mission to which they can contribute. We know young workers feel strongly about sustainability issues. So as companies and industries increasingly tackle green initiatives (more about these in a moment), CHROs and other leaders should seek candidates to whom climate change and sustainability are important. 

To truly achieve these steps, organizations should take a long-term approach to pre-skilling emerging talent. This involves identifying critical thinking, creativity, collaboration, communication, and emotional intelligence as key skills to develop before they are absolutely required on the job. Dedicated pre-skilling programs, rotational assignments, project-based learning, and partnerships with education providers can cultivate these human skills in the talent pipeline.

Forward-looking companies will treat pre-skilling as an investment, not an expense. Though establishing this initiative requires effort and resources before skills are needed, it pays dividends through more adaptable talent who can learn continuously as needs evolve.

Embracing the New Tools

How can organizations transition from old ways of thinking to address the skills gap creatively? This question serves as a perfect segue to the growing role of AI in talent identification. When utilized effectively, AI can broaden the pool of potential candidates, making the hiring process more inclusive. However, it's crucial to ensure that AI complements human interaction rather than dehumanizes it. To achieve this, organizations should harness AI's capabilities for providing candidates with feedback, enhancing their self-awareness regarding their career development, and making the hiring process more candidate-centric.

Even more importantly, special attention and care must be applied to sanitizing the training data that AI ingests so it neither replicates nor scales human biases. While AI has faced legitimate accusations of bias in certain instances, it's essential to acknowledge that human hiring managers and recruiters are inherently biased as well. They tend to favor candidates who resemble them, a challenging bias to overcome, as managers naturally wish to claim their hires as the cream of the crop.

As an alternative approach, consider training AI algorithms to prioritize attributes like hard and soft skills and values that the company should have, rather than fixating on past hiring criteria. In essence, AI can be optimized to identify qualities that may have been overlooked previously. This brings us back to the importance of changing your thinking and reengineering your habits.

At ManpowerGroup, we have extensive experience meeting with and evaluating jobseekers. Generative AI is one of the tools we use, and it’s instructive that when we do, candidates often don’t realize it. Correctly managed, generative AI can be more personable than other recruiting processes. Today, after all, jobhunters typically shotgun out hundreds, even thousands, of resumes in hopes of pleasing a mysterious algorithm. More often than not, they hear nothing back. That’s worse than impersonal—it’s cruel.

Contrast this with a well-designed generative AI system. The algorithm is tuned to uncover soft and adjacent skills that may help fill a need in the hiring company. It is empathetic and curious. When candidates don’t make the cut, the generative AI provides feedback as to why, helping them improve their interviewing skills.

Case in Point: The Green Revolution

We are fortunate to be early in a period that will allow—even force—forward-looking employers to put all this advice into practice.

The rising green economy is a beautiful cauldron of innovation and adaptation. Whether you’re talking about vertical farms, offshore arrays of solar panels, or the infrastructure needed for electric vehicles, there are not only jobs but companies and even industries that don’t exist yet—but will soon. And the green revolution isn’t just for born-digital organizations; due to regulatory pressures, consumer demand and the simple desire to do the right thing, leaders in all industries face challenges around sustainability.

On the skills front, what all this means is that job categories we have yet to consider will crop up and will do so quickly. Obviously, there is no existing pipeline for credentialed workers to fill these positions. That means CHROs and other leaders will have to think outside the box to find the skills they need.

Reskilling needs to happen in tandem with technology adoption—gradual implementation paired with reskilling opportunities maximizes human potential. Cross-training displaced workers into related roles retains institutional knowledge. Investing in reskilling today ensures critical talent transitions are supported.

​

Looking Ahead

Digital transformation, changing attitudes toward sustainability, demographic trends, and workers who want to feel like they’re not just making widgets have created interesting times. It’s understandable for business leaders to bemoan what they view as a dearth of qualified candidates. But those who stop looking at credentials and start studying potential will lead the way and gain a lasting competitive edge.