AI is changing who you should hire. Here’s how to get it right

That’s not a job description. That’s a superhero spec. And the person most organizations reach for to fill it—the candidate with deep sector experience, the safe hire, the one who’s “done this before”—is often exactly wrong for what the role now requires. The logic behind the experience filter is not irrational. Sector knowledge compresses ramp time. It signals credibility with peers. It reduces the number of things that can go wrong in the first ninety days. When the environment was stable and execution was the output, it was a reasonable proxy for readiness. That environment is gone. AI has compressed execution timelines and put judgment at the center of competitive advantage. The work that once required a team now requires one person with the right capabilities. And the capabilities that matter most—operating without a playbook, making decisions under uncertainty, building alignment across functions—are not what the sector-experience filter selects for. It selects for pattern reproduction. In roles that now require pattern disruption, that’s not risk reduction. It’s risk amplification. New criteria A recent Strategy Science study, summarized by HEC Paris, found that within-industry breadth combined with cross-functional experience predicts stronger strategic foresight than narrow same-sector depth—particularly under conditions of uncertainty. The implication is uncomfortable: the profile most organizations default to in hiring may be the profile least suited to the moment they’re hiring for. The middle management layer is where this mismatch is most expensive. These are the p