In brief
- AI is already in most hiring processes: writing job posts, sorting resumes, suggesting questions, ranking candidates.
- At each step, it works from what you’ve defined. If you haven’t defined how people succeed at your company, it fills the gap with generic answers.
- AI doesn’t create new hiring problems. It makes the ones you already have happen faster and at a bigger scale.
Hiring is usually the first place a company puts AI to work. It’s easy to see why. Job posts take time to write. Resumes pile up. Interviews are hard to schedule and harder to compare. AI makes all of that faster.
But faster only helps if you’re moving in the right direction. Most companies have never written down what it takes to succeed at their company, beyond the skills on the job description. So when AI steps into the hiring process, it has nothing to go on for the part that decides whether a new hire works out.
As I wrote in AI Won’t Fix Your Culture, AI gives you more of what you already measure. In hiring, that shows up in four places.
1. The job post
Ask AI to write a job post and it will give you a clean, professional draft. It will also list the same soft skills every other company lists: team player, strong communicator, self-starter, detail oriented.
Those words describe almost anyone, so they attract almost anyone. They were already the weak spot in most job posts. They’re the job requirement nobody wrote down, and now AI writes them down generically, in seconds, for every role you post.
What to give it instead: the behaviors your best people in that role actually show. Not “strong communicator,” but what good communication looks like in that job at your company. A post that describes how the work gets done here attracts the people who want to work that way.
2. Screening
Ask AI to find your strongest candidates and it will look for patterns in what you’ve hired before: titles, years of experience, schools, industries, keywords.
The problem is that resumes only show what someone has done, not how they did it. And your past hires include the ones who didn’t work out. AI can’t tell the difference, because nobody recorded why some hires succeeded and others didn’t. So it screens for more of the same, the good matches and the bad ones together.
What to give it instead: what success looks like in the role, in behaviors, alongside the skills and experience you need. Then candidates are filtered against the job as it’s really done, not only against the resumes of the people who held it before.
3. Interview questions
Ask AI for interview questions and you’ll get a solid list. Tell me about a time you handled conflict. How do you prioritize competing deadlines. Where do you see yourself in five years.
Every candidate has heard those questions, and most have practiced the answers. The questions are generic because AI doesn’t know which behaviors matter at your company. So the interview tests how well someone interviews, not how they’ll work with your team.
What to give it instead: the specific behaviors you want to probe for that role and level. Then AI can help you write questions that ask for real examples of those behaviors, and you can hire for the culture you’ve actually named.
4. Scoring candidates
Many tools now rank or score candidates after the interview. AI can only score what it’s been told to look for, and in most hiring processes that’s skills and experience.
So the candidate with the strongest resume ranks first, even when the interviewers had doubts about how that person would work with others. Those doubts never made it into the score, because there was no place to put them. That’s how a company ends up with a hire who looked right on paper and didn’t work out anyway.
What to give it instead: a rating for each behavior, scored by the interviewers against the same standard. Then how someone works counts alongside what they’ve done, and the score reflects the whole picture.
AI will be in your hiring either way
Most companies aren’t deciding whether to use AI in hiring. They’re already using it, or their applicant tracking system is using it for them. The real decision is what it amplifies.
If you haven’t named your culture, AI will amplify the generic job posts, the resume matching and the standard questions you already have. You’ll hire faster, and you’ll keep running into the same problem: people who look right and leave, or stay and never fit how the work gets done.
If you have named it, AI becomes useful in a different way. It helps you describe the behaviors in every job post, screen for them, ask about them and score them, consistently, across every role and every hiring manager.
It all starts with naming your culture. Here’s how hiring works when it’s built around the culture you’ve named.
Read next: How to Hire for a Culture You’ve Actually Named
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