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What a million assessments say about hiring the class of 2026

June 5, 2026
in Human Resources
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What a million assessments say about hiring the class of 2026
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The class of 2026 may be the most AI-ready workforce cohort employers have ever seen, yet many hiring processes aren’t built to find them.

Matt Kirk, head of market insight and solutions at global talent assessment firm SHL, draws that conclusion from more than a million assessments across roles and geographies, and he says organizations are missing a significant opportunity as a result.

SHL’s data show graduates consistently outperform non-graduate peers on the behavioral skills most tied to AI readiness, Kirk says. That finding is reshaping how leading employers approach early-career hiring. “It is no coincidence that many organizations are actively increasing their graduate intake,” he says.

Graduates are ‘willing and ready’

Employers saw a 26% increase in applications in 2025, according to the National Association of Colleges and Employers in a survey sponsored by Indeed, driven largely by AI tools that let candidates apply at scale with minimal effort. The research found that 70% of candidates now use AI at some stage of hiring, producing applications that are increasingly polished and increasingly identical.

Matt Kirk, head of market insight and solutions at SHL

Some employers are responding by closing requisitions early to manage volume, a tactic that may be filtering out the strongest candidates. AI-assisted applicants move fast, often within minutes of a role going live. More deliberate candidates apply later and miss the window, leading to a talent funnel that rewards speed over quality.

Kirk says these conditions are exactly why graduate hiring deserves a closer look. Graduates tend to be more digitally native, more oriented toward continuous learning and better positioned to get real value from AI tools. “That adaptability is invaluable,” says Kirk.

Read more: 52% of employees call themselves AI experts—but are they?

The screening problem

The catch is that traditional screening methods weren’t built for this environment. AI-optimized CVs reveal little about the candidate behind them. Closing pipelines early to manage inbound volume risks, eliminating the people most worth hiring.

Kirk says the path forward is straightforward when HR teams assess the behaviors that predict performance, not just the credentials that signal effort. “For talent teams serious about building a workforce that can work with AI rather than simply alongside it, the evidence points in one direction,” he says. “Invest in graduates, and measure the behaviors that prove it.”


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