Plenty of people are good enough to do the job. The problem is, they don’t look the part. Or they don’t sound polished enough in the interview. Or their CV isn’t wrapped in the right buzzwords. So they get overlooked.
And that’s not just unfortunate. It’s a productivity problem hiding in plain sight.
We talk a lot about talent shortages. About how hard it is to find people who can actually get things done. But Gallup’s research says otherwise: teams leveraging AI and automation tools deliver 1.7x more output with 20% fewer people and generate 23% more profit. The talent exists. What's broken is how we find and assess it.
The hiring process, for the most part, is still stuck in the past. Filtering for polish. Screening for credentials. Interviewing for confidence. None of these reliably predict who will perform. In fact, over 85 years of data prove that resumes and traditional interviews are incredibly poor at forecasting job success.
We’re still filtering for surface-level signals. We’re drawn to candidates who present well, follow familiar patterns, and fit the traditional mold whether or not they’re actually best equipped to perform.
Ironically, the very traits business leaders say they’re looking for, AI fluency, tool mastery and adaptability are the ones most likely to go undetected by traditional hiring filters. High-impact talent gets ignored, while surface-level signals still drive decisions.
We’re seeing a massive shift in what matters. Experience still counts but mastery, curiosity, and adaptability now signal more than a polished CV ever could.
Harvard Business School research shows that curiosity leads to better decisions and more creative problem-solving. The Korn Ferry Institute found that orgs with highly agile executives outperform their peers with 25% higher profit margins. These aren’t soft traits. They’re predictors of who will learn fast, adapt quickly, and drive results.
And yet, the hiring process still penalizes people who haven’t learned to play the game.
It’s not enough to say we want builders. We need hiring systems that can spot them. Systems that filter for capability, not charisma. For tool fluency, not brand names. For real-world execution, not verbal gymnastics.
In a world where 75% of professionals already use AI at work, the gap isn’t in access, it’s in mastery. Most candidates are “novices” or “explorers.” The small group of builders combining intelligence, curiosity, and AI fluency are already driving exponential output.
So what are we actually doing to surface them?
Traditional methods i.e resumes, interviews, even psychometric tests are either easy to fake, hard to scale, or both. Situational Judgement Tests have better predictive validity, but they’re often static and easily gamed with AI help. Work samples come closer, but they’re logistically hard to scale.
We’re stuck between gameable and impractical.
The candidates don't need more polish, it’s hiring teams that need better filters
Filters that highlight productivity. Signals that reward mastery, not mimicry. Hiring tools that reflect how work actually gets done today... fast, adaptive, tech powered.
Because the people who are good enough to do the job are everywhere. But until we stop screening for polish and start surfacing performance, they’ll keep getting missed.
And the orgs that figure this out first will hire faster, build smarter, and outpace the competition without needing to fight for talent that was there all along.
