Hiring Processes Miss the Class of 2026 — SHL Data Says Graduates Are Your Best AI Bet
The News
The class of 2026 may be the most AI-ready workforce cohort employers have ever seen, yet most hiring processes are not built to find them, according to Matt Kirk, head of market insight at global talent assessment firm SHL. Writing in HR Executive, Kirk draws the conclusion from more than a million assessments across roles and geographies.
SHL's data shows graduates consistently outperform non-graduate peers on the behavioural skills most tied to AI readiness — including digital adaptability, continuous learning orientation, and ability to work with AI tools effectively. Kirk says this is no coincidence and notes that many leading employers are actively increasing graduate intake. However, the same forces making graduates attractive — AI literacy and rapid application habits — are also making them harder to identify through traditional screening.
Employers saw a 26% increase in applications in 2025, driven largely by AI tools that let candidates apply at scale with minimal effort. The National Association of Colleges and Employers, in a survey sponsored by Indeed, found 70% of candidates now use AI at some stage of hiring. Some employers are responding by closing requisitions early to manage volume — a tactic that may filter out the strongest candidates. AI-assisted applicants apply fast; more deliberate candidates, including quality graduates, apply later and miss the window.
Why It Matters
This is the kind of data point that should reshape how you think about early-career hiring. If your standard response to application surges is 'close the req when we hit 500 applicants,' you are systematically filtering out the candidates most likely to succeed in an AI-enabled workplace — the very graduates SHL's million-assessment dataset says are your best bet.
The practical problem is acute: AI-generated CVs look perfect but reveal nothing about actual capability. AI-optimised applications flood the funnel. Traditional screening rewards speed over quality. And the genuine AI-ready graduates — who tend to be more deliberate, more thoughtful, and less likely to spray applications — are getting squeezed out by process design that was built for a pre-AI world.