AI in hiring: Speeding up recruitment, risking blind spots — why the human touch still wins
The problem with how AI is used in hiring today
According to Mercer Mettl (2024), 72% of recruiters say that while AI has increased hiring speed, it has actually lowered the quality of profiles reaching the interview stage.
Many things are going wrong. For instance, there is an over-reliance on keyword matching. Resume gaps are getting penalised without context. Biases are being baked into algorithms, especially around age, career breaks, or non-linear journeys.
AI isn't neutral by default — it reflects the data it's fed. If more women list parenting breaks, then AI filtering on continuous employment will disproportionately screen them out, even when they are equally or more qualified.
What AI is actually good at
I asked Vivek Pandey, Vice-President, Human Resources, Dream11 who shared – 'While hiring, AI saves the initial screening and shortlisting time for junior level positions. However for mid and senior levels, it has to be clearly the ability of the talent acquisition teams to make an assessment. AI cannot replace the human element which is being sensitive to areas like work culture fitment, and traits like leadership, collaborative working and teamwork'.
Let's not throw the baby out with the algorithm. AI is highly effective when used for: parsing structured data from thousands of resumes; creating job descriptions quickly and at scale; scheduling interviews and automating logistics; and flagging missing skills or formatting issues.
What AI should and should not be used for
What it should not be used for: final shortlisting; cultural-fit decisions; rejection decisions based on timelines alone; screening out returnees or career shifters. AI can scan, but it can't sense.
AI can't see potential in a messy story or pick up on emotional intelligence. It can't understand career transitions or sabbaticals or ask clarifying questions in a grey area.
Good hiring is about contextual judgment. A resume doesn't tell the full story. A conversation often does. Great TA teams know when to use data and when to trust their instinct.
How talent aquisition teams can stay relevant
Here are steps to modernise your hiring without compromising the human lens: Train recruiters in AI literacy; know how the filters work, what's being excluded, and how to write better prompts.
Audit your AI stack quarterly. What's being filtered? What's being missed? Fix the blind spots. Create a Human+AI hybrid SOP, where AI assists the screening and recruiters make the decisions.
Candidates should know what's automated and what's human. Transparency creates trust and trust creates better candidate experiences.
Conclusion
AI can power your hiring engine, but humans still need to drive it. The future of recruitment doesn't lie in choosing between technology or people. It lies in knowing when to let machines support and when to let people lead. Because in the end, great hiring has always been about one thing: understanding people.
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