Key takeaways
- AI makes sourcing faster and wider, so finding names is no longer the hard part.
- Application floods and identical AI polished resumes have pushed signal to noise down.
- Candidate fraud is a real hiring risk and needs identity checks built into the process.
- The winners combine AI speed with human screening, references and live technical conversations.
The short answer: both
People ask me this question in many different ways. Is AI helping recruiters? Is it killing the resume? So here is my honest answer. AI has made it easier to find people and harder to know people. Those are two different jobs, and most hiring teams only upgraded the first one.
If you are a company hiring IT resources, or a vendor submitting candidates to a prime vendor or MSP, you feel both sides every week. Searches that took a full day now take few minutes. Plus the inbox is full of resumes that all look perfect. So which way is it going? Let me break it down.
Where AI makes finding talent easier
Faster search and matching
Modern sourcing tools read a job description and pull matching profiles across job boards, your ATS and public networks. Boolean strings still matter, but AI ranking means a recruiter can get to a short list much quicker. For common roles like Java developers, QA analysts or business analysts, the first pass is almost instant.
Wider reach
AI also widens the net. It surfaces people with adjacent titles, people who describe the same skill in different words, and people in other cities who are open to remote or hybrid work. For niche needs like healthcare integration or revenue cycle systems, that wider reach is a real help.
Less admin work
- Scheduling: interview booking and reminders run on their own.
- Notes: call summaries and screening notes get drafted for you.
- Outreach: first messages can be personalized at scale, then a human follows up.
Where AI makes it harder
The application flood
The same tools are in the hands of candidates. One click apply, AI cover letters and auto apply bots mean every posting gets more applications than any team can read. Korn Ferry, citing LinkedIn data, reported that the platform was seeing an average of 11,000 applications every minute. Volume went up. Quality per application did not.
Identical, polished resumes
When thousands of people ask an AI tool to tailor a resume to the same job description, you get resumes that read the same. Every bullet matches the keywords. Every summary says "results driven." So the resume stops being a signal of fit, and becomes a signal that someone used a tool. I have seen hiring managers reject good people because their resume looked too much like the twenty before it.
Fraud and fake candidates
This is the part that worries me most. Fake profiles, borrowed identities, proxy interviews and deepfake video calls are now a real risk, especially for remote IT roles. In a Gartner candidate survey, 6 percent of job seekers admitted to interview fraud, and Gartner predicts that by 2028 one in four candidate profiles worldwide will be fake. For a staffing vendor, submitting one fraudulent candidate can damage a client relationship that took years to build.
So, net view: easier or harder?
My view is that finding talent got easier, and trusting talent got harder. The total effort did not go down, it moved. Less time goes into searching. More time has to go into verifying and assessing. Teams that did not move that time are the ones complaining that "AI ruined hiring."
What works now for companies and vendors
Here is the process we follow and recommend. None of it is fancy. It just puts humans where AI is weak.
- Use AI for the first pass only. Let it rank and shortlist. Do not let it make the final call on who gets submitted.
- Talk before you submit. A real phone or video call with the recruiter, camera on, asking about actual projects. Ask what they built, what broke and how they fixed it. Polished resumes fall apart fast when the person cannot explain them.
- Verify identity early. Check government ID against the person on video, confirm work authorization, and match LinkedIn history with the resume. Do it before the client interview, not after the offer.
- Check references that you find yourself. Do not only call the numbers the candidate gives you. A former manager found through your own network is worth more.
- Use short practical assessments. A live problem, a requirements walkthrough for a BA, a test case review for QA. Keep it short and relevant to the role.
- Keep a bench of known people. Consultants you have already placed and verified are worth more than a thousand new applicants. Stay in touch with them.
What this means for vendors in the supply chain
If you are a tier 2 vendor working through a prime vendor or MSP, the bar went up. Primes are getting the same flood of submissions, so they trust vendors who send fewer, cleaner candidates. Speed still matters. But one fake candidate can get you removed from a program. So your value is not how many resumes you can push in one hour. Your value is that every person you submit is real, available, authorized to work and actually able to do the job.
That is also why we keep consultants on our own W2 payroll when it fits the engagement. It means we know who they are, we have done the paperwork, and we stand behind them. You can read more on how we work with primes on our vendor partners page.
Final thought
AI is a tool, and like any tool it rewards the people who use it with judgment. Use it to search faster. Then spend the saved time on the human part, talking to people, checking who they are and testing what they can do. That is where good hiring still happens. If you want to see how we approach screening in practice, take a look at our IT staffing services.
Frequently asked questions
Is AI making it harder to hire good IT candidates?
AI makes sourcing faster, but it also floods roles with similar looking resumes and raises fraud risk. Hiring is not harder overall, but more of the effort now goes into verification and assessment.
How can employers spot AI generated or fake candidates?
Hold an early screening call with the camera on, ask detailed questions about real projects, verify ID and work authorization, and check references you find yourself. Short practical assessments also help.
Should recruiters stop using AI tools?
No. AI is very useful for search, ranking and admin work. The final decision on who gets submitted or hired should still involve a human who has spoken with the candidate.
Need screened, verified IT talent?
We combine fast sourcing with real conversations and identity checks before any submission. Tell us about your role.
Israr Kazmi
Israr Kazmi is the founder of iCareTechno, the IT staffing, recruitment and consulting division of iCareBilling LLC in Chicago. He writes about hiring, vendor relationships and careers in IT.
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