AI Overwhelms Recruiters and Frustrates Jobseekers

RNZ reports that some jobseekers feel dehumanised by recruitment processes where automated screening appears present but opaque. A Wellington graduate identified as Sam told RNZ she has been searching for more than a year and receives many standard rejection emails; she said typical applicant counts are 150 to 300, and some listings showed over 800 applicants. RNZ also quotes Sarah Wrightson, a CV-writing business owner in Te Awamutu, who said her customer base is up 50 percent compared with last year and that CVs are being rejected when they do not match keywords, job titles or formatting.

Industry-pattern observations: Applicant-tracking systems and automated resume parsers commonly use keyword matching, entity extraction, and simple ranking heuristics. Generative AI lowers the marginal cost of producing application materials, which can inflate applicant volumes and increase false positives and false negatives in keyword-driven filters. Companies using opaque automated screening can create candidate uncertainty about whether a human has reviewed an application, a dynamic that has implications for candidate experience and employer brand.

For recruiters and HR-technology teams, the RNZ reporting highlights two trade-offs seen across the sector, automation reduces manual workload but can introduce brittle filtering rules and poor candidate experience. For vendors of ATS and resume-scanning tools, continued reliance on surface-level keyword matching risks filtering out qualified candidates whose documents do not conform to narrow parsing expectations. For jobseekers, the reporting illustrates why paid CV services have become more sought-after in some local markets.

• •Trends in ATS vendors adopting semantic matching or embedding-based ranking to reduce keyword brittleness
• •Signals from major job boards about policies or transparency features for automated screening
• •Shifts in candidate behaviour, such as increased use of professional CV services or tailoring for parsers
• •Employer disclosures or legal/regulatory activity on algorithmic fairness and transparency in hiring