ORLANDO, Fla. — The American labor market is often described as having a talent shortage. Employers say they cannot find enough qualified workers, while many workers say they apply for jobs and hear little back.
Those two complaints may sound like opposites, but they often point to the same problem: hiring systems are not always good at matching people to the right roles.
As of early 2026, the United States continues to report millions of open roles alongside persistent underemployment. In many industries, companies still struggle to find workers while capable candidates fail to make it through screening systems.
Yunan Weng, chief human resources officer at Yanwen Express, said the issue often starts with how hiring systems evaluate people.
“Many employers still operate with a ‘sorting first’ model,” Weng said. “They reduce a candidate to a few signals, then make exclusion the first step. That might help with volume, but it leads to poor matching.”
That approach can create problems beyond the initial screening process. When the wrong candidates are filtered out, or the wrong matches are pushed forward, the effects can show up later in training, performance and retention.
“Workers don’t experience hiring and engagement and on-the-job training as separate things,” Weng said. “A mismatch at the hiring stage will show up later in performance, as manager load, and eventually as turnover.”
One challenge is that employers and job seekers often describe the same skills in different ways. Companies may rely on job titles, credentials or keyword filters, while candidates may have experience that does not fit neatly into those categories.
Weng said that creates a language problem in hiring.
“Employers describe roles one way, candidates describe themselves another, and the system can’t reconcile the two,” Weng said. “Once that gap enters the process, the technology built around it often reinforces the mismatch instead of fixing it.”
That can make the labor market look tight even when qualified workers are available. In some cases, employers are not failing to attract talent. They are failing to identify it accurately.
Weng argues that hiring systems should be connected more closely to onboarding, training, performance and retention data so companies can better understand which candidates are likely to succeed.
That approach is reflected in findings from Weng’s research, which focuses on how continuous feedback systems and predictive analytics can support retention and employee development when used in integrated HR environments.
Weng said artificial intelligence could help companies identify skills more accurately, but only if it is used to improve judgment rather than simply automate rejection.
“Not every labor issue is a pipeline issue,” Weng said. “Sometimes employers do need more trained workers. But there are plenty more cases where the labor exists and the matching process doesn’t suffice.”
Weng said companies that want broader access to talent need to rethink how they evaluate people across locations, backgrounds and career paths.
As more companies add AI to HR and recruiting, the question is whether those tools can help employers recognize qualified workers who may otherwise be filtered out.
For Weng, the future of hiring depends on building systems that connect recruitment, employee development and retention instead of treating them as separate problems.
“The harder question is whether AI can support better judgment at the points that matter most,” Weng said, “and whether it can help people move into the right work with a stronger chance of staying and growing there.”
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