FEATURE an application can be submitted with one click, people apply more broadly, more speculatively and with less consideration of fit. The friction that once served as a natural filter has been engineered away.
The automation trap
At the same time, candidates quickly learn how automated screening works, and they optimise for it. More keyword-matching, more CV padding and more applications per person, which generates more volume for employers to manage. This, in turn, again prompts more automation.
Louis Allain, VP Product, Welcome to the Jungle
The logical response from employers has been to automate the other side of the equation too. If candidates are using AI to generate applications at scale, use AI to screen them at scale too. Deploy an ATS, score CVs automatically, set keyword filters and accept or decline at volume.
What gets lost in this exchange is exactly what both sides are actually looking for: a genuine match. Not a CV that clears a filter, but a person who will thrive in the role and the organisation.
The cost to business
This is where the cycle tightens. Automated screening tools, particularly those trained on historical hiring data, tend to replicate the patterns of past decisions. They learn what previous hires looked like and filter for more of the same.
For CXOs, the implications of this cycle extend well beyond recruitment. Poor hiring decisions are expensive – the cost of a mis-hire at a senior level is routinely estimated at multiple times annual salary when you factor in lost productivity, team www. intelligentcxo. com
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