How Tech Companies Build Their Recruiting Stack
AI hiring has moved beyond adding “machine learning” to a job description and waiting for qualified candidates to apply.
Tech companies now face a more complicated problem: the AI skills they need are often concentrated among relatively small groups of people, those skills can change quickly, and the same job title may mean very different things from one company to another. A software engineer who has experimented with a language-model API isn’t necessarily ready to build production AI systems. Likewise, a data scientist with years of statistical experience may have capabilities that a rigid résumé filter misses.
The demand data shows why recruiting teams are rethinking their approach. According to SHRM research, 28.5% of U.S. IT and computer-science job postings mentioned AI skills, the highest average share among the 27 countries studied. Yet demand varied sharply by specialty and country.
That uneven demand creates a recruiting challenge that conventional applicant-tracking...
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