Skills-based hiring meets AI: What matters now

We’ve talked about skills-based hiring for years. Strip away degree requirements, focus on what people can actually do, open opportunities to non-traditional candidates. But AI is changing what “skills” means.

The new paradox

AI makes it easier to demonstrate skills through work samples and real-time assessments. But it also makes it harder to tell whether you’re assessing the candidate’s skills or AI’s capabilities. That brilliant writing sample or data analysis — did they create it, or did AI?

The skills that matter most

In the AI age, we need to change our evaluation from “can they do this task?” to “can they do this task while effectively collaborating with AI, and do they know when human judgment should override the technology?”

Critical skills now:

Critical thinking: Can they evaluate AI outputs and improve on what AI generates?
Judgment: Do they know when to use AI vs. when to trust human intuition?
Adaptability: As AI capabilities expand, can they continuously learn?
Problem-solving: Can they break down novel problems AI hasn’t been trained on?

Implementing real skills-based hiring

Test in real time: Give candidates problems to solve during interviews. Watch how they use AI (if you allow it). That tells you a lot.
Focus on process, not just product: Ask candidates to walk you through their approach. Their explanation reveals whether they understand the work or just know how to prompt AI.
Verify across multiple situations: One impressive sample might be AI-generated. Consistent capability across varied situations shows genuine skill.
Be transparent: Tell candidates what level of AI assistance is acceptable and expected.

The opportunity

Skills-based hiring is more achievable than ever if we redefine what “skills” means. Rather than focusing on task completion, focus on delivering value in a world where AI is a constant collaborator. Organizations that figure this out first will have a significant advantage in attracting and developing talent.