A lot of candidates are frustrated right now. They apply for roles they are qualified for and never hear back. They get rejected quickly, sometimes automatically, and assume AI removed them from the process before a human ever looked at their resume.
On the other hand, companies are frustrated too. Hiring still feels slow. Strong candidates seem to disappear. Interviews do not always match what the resume promised.
Both sides are pointing at AI.
The reality is more complicated.
AI is not coming to hiring. It is already here. Companies are using it to screen resumes, rank candidates, and move faster. Candidates are using it to rewrite resumes, prep interview answers, and try to beat the system before a human ever gets involved.
What is missing in most of these conversations is clarity.
AI is not good or bad on its own. But when it is layered on top of unclear roles, rushed decisions, and vague expectations, it does not fix the problem. It amplifies it.
AI Is Already in the Room
Most organizations are already using AI in hiring, whether they realize it or not. It may be built into an applicant tracking system, resume screening software, or recruiting platform designed to save time.
At the same time, candidates are using AI just as actively. Common uses include:
- Rewriting resumes to better match job descriptions
- Optimizing language to get past screening tools
- Practicing interview answers
- Preparing behavioral responses
Both sides are using the same tools, often without shared expectations or clear boundaries. That is where things start to break down.
When the Job Isn’t Clear, AI Can’t Be Either
AI can only work with what it is given. In hiring, that usually starts with a job description.
The problem is many job descriptions are not written for clarity. They are written to get something posted. They are pulled from templates, stitched together from old roles, or built around long lists of skills without priorities.
When that happens, AI does not create alignment. It screens efficiently against vague criteria.
AI does not know:
- What success actually looks like in your organization
- Which skills matter most versus least
- How the role functions day to day
- What problems the person is meant to solve
AI does not clarify roles. It amplifies whatever clarity or confusion already exists.
How Candidates Are Using AI and Where It Gets Complicated
Most candidates are not using AI to be deceptive. They are using it because they know the system is automated.
Many job seekers paste their resumes into AI and ask it to better match a job description. From their perspective, it feels necessary just to get past screening tools and into a real conversation.
The issue is what gets lost along the way.
When AI rewrites a resume to closely mirror a role:
- Language becomes more polished and more generic
- Skills can sound stronger than they really are
- Responsibilities may feel inflated
- The resume matches the job, but not always the person
That creates tension on both sides. Hiring teams believe they are interviewing a strong fit. Candidates feel pressure to perform as a version of themselves that may not be fully accurate. And when interviews go deeper, gaps appear.
Often, those gaps are not about ability. They are about misalignment created earlier in the process.
What AI Will Always Miss
AI is good at data. It is not good at people.
A resume can show what someone has done. It cannot show:
- How they make decisions
- Why they care about the work
- How they respond under pressure
- How they adapt when things change
In roles where judgment, empathy, accountability, or leadership matter, those gaps matter more than ever.
When companies rely too heavily on AI screening, they risk filtering out candidates who do not market themselves well but perform exceptionally. They overvalue polish and undervalue motivation, values, and behavioral fit.
When you screen only for skills, you fill seats.
When you screen for behavior and motivation, you build teams.
The Interview Problem AI Creates
Hiring teams are starting to notice patterns:
- Answers sound polished but lack depth
- Examples do not hold up under follow-up
- Candidates who struggle once the script ends
As AI becomes more common, interviews have to change. They cannot reward memorized responses. They need to test how someone thinks, adapts, and explains their reasoning in real time.
Responsibility Lives on Both Sides
This is not about banning AI. It is about using it intentionally.
For companies, that means:
- Being transparent about how AI is used
- Clarifying roles before automating hiring
- Designing interviews that test thinking, not memorization
For candidates, that means:
- Using AI as a support tool, not a replacement
- Understanding your own experience well enough to talk about it
- Expecting deeper, more probing interviews
The more automated the front end of hiring becomes, the more human the decision-making needs to be.
Takeaway
AI can make hiring faster. It cannot make it better on its own.
Clarity still matters. Behavior still matters. Human judgment still matters.
That is where a clear hiring process makes the biggest difference. Not one built around tools or trends, but one that forces leaders to slow down long enough to define what they actually need before automation enters the picture.
At The Metiss Group, this is exactly what The Hiring Process Coach™ helps teams do. We work with leaders to clarify roles, define success, and align on behaviors before resumes are screened or interviews begin. When that foundation is clear, AI can support the process instead of driving it.
The future of hiring is not AI versus people.
It is AI plus leaders who are clear on who they are hiring, why they need them, and how they will know when they made the right choice.
AI can help someone get in the door.
It should not be the one deciding who belongs inside.
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