
Over 70% of CVs are AI-polished, killing resume signals. Recruiters rely on interviews and assessments. Assessment platforms gain; pure ATS vendors face commoditization.
The resume's value as a hiring signal is eroding. Over 70% of white-collar candidates now use AI to draft their CVs, according to data from Hunar.AI. Among Gen Z, the figure exceeds 85%. When every resume is keyword-optimised to the same standard, recruiters can no longer distinguish strong candidates from polished ones. The consequence is structural: HR technology vendors that depend on resume-based screening face obsolescence, while assessment and interview-first platforms capture rising demand.
The applicant tracking system (ATS) filter was built to rank candidates on keyword density and formatting. AI resume tools have turned those advantages into baseline expectations. Vinay Jain, co-founder of NexxaScreen, reports that candidates with ATS-optimised resumes now receive 5x to 10x higher shortlist visibility than before, even when holding the same underlying experience. Application volumes surge. The ratio of qualified candidates to total applicants in the top of the funnel drops.
When all resumes tick the same keyword boxes, the ATS cannot rank candidates by actual fit. Krishna Khandelwal, founder and CEO of Hunar.AI, describes the result: “when everyone’s resume is polished to the same standard, recruiters are scanning identical templates.” The resume loses its differentiating power. Recruiters respond by looking for gaps between the polished profile and live conversation.
“Since candidates upload resumes before entering interview rounds, we often notice a gap between how strong a profile appears on paper and how a candidate performs in conversation,” Jain notes. Recruiters are spotting templated language more often. Spotting it does not solve the fundamental problem: the resume no longer carries reliable information about ability. The market for resume-parsing ATS products becomes commoditised.
The structural change creates a natural wedge in the HR technology market. Vendors built on resume parsing face margin compression. Platforms offering AI-led interviews, situational assessments, and skills-based evaluations see rising demand.
HirePro, an assessment platform, reports an increase in flagged suspicious behaviour during online tests: from 32.4% of candidates in 2021 to nearly 45% in 2025. The rise in bad-faith applications forces employers to invest in proctored, interactive evaluations. Pasupathi S, HirePro’s chief operating officer, says the real challenge is “separating signal from noise, identifying candidates who possess genuine capability, adaptability, and long-term potential.”
NexxaScreen sends its AI interview to 70 or 80 candidates who cleared the paper shortlist. Jain notes that “several strong candidates are sitting in that rejected pool because their resume did not survive the first filter.” For HR tech buyers, investing earlier in assessment technology reduces the cost of false negatives.
LinkedIn research shows 74% of recruiters struggle to find qualified candidates even as hiring activity runs 40% above pre-pandemic levels. Among recruiters who say hiring has become more difficult, 53% point to a surge in AI-generated applications, while 47% cite shortages of in-demand skills. Hiring teams lean harder on referrals, previous company brands, and portfolio reviews. Professional networking platforms and skills-assessment tools capture more of the hiring value chain at the expense of resume databases.
AI-enhanced screening introduces unintended bias. The source explicitly states: “AI did not create bias, it made existing biases faster and more invisible.” Two groups bear the cost.
Name Recognition Blind Spot. International candidates who held roles at unicorns or large companies in their home markets are auto-rejected because the ATS does not recognise the employer names. The filter treats unfamiliar brands as missing signals. This creates a false negative that the candidate cannot fix with keyword stuffing.
Keyword Ceiling for Career Switchers. Career switchers, even after aggressive AI resume optimisation, face a hard limit. If their background is in a different industry, the job description keywords are not in their history. No amount of formatting can insert industry-specific terminology absent from their work experience. These candidates fall through the gap regardless of their ability.
The signal collapse in resume-based screening creates a clear winner and loser in HR technology. Assessment platforms with high revenue from AI interviews and skills tests have a tailwind. Pure ATS vendors face declining renewal rates unless they pivot.
Investors tracking this space should focus on the proportion of revenue derived from assessment products rather than resume parsing. A threshold above 30% suggests the vendor is positioned for the shift. Declining renewal rates for legacy ATS contracts confirm the thesis. Earnings calls that mention “skills-based hiring” or “interview-first workflows” as a strategic priority indicate management alignment.
Two risks could revive the resume as a useful signal. First, ATS vendors could integrate generative AI that parses actual skills and experience beyond keywords. A tool that evaluates capability rather than keyword density would restore the resume’s differentiating power. Second, regulatory pressure could force companies to maintain resume-based screening or to provide transparency in automated decisions. Both risks are real but not yet priced.
Khandelwal and Jain both describe a system where a 15-minute voice conversation reveals more about a candidate than a resume ever could. The companies that build the infrastructure for that conversation – and for the assessments that precede it – will own the next phase of HR technology. The rest will be fighting over a shrinking slice of a market that already knows its filters are broken.
For broader context on sector rotation and technology shifts, see AlphaScala’s stock market analysis.
Prepared with AlphaScala editorial tooling from the source reporting linked above. Indexable analysis may include a cited Alpha Score value. Publishing checks screen each story before release. Educational coverage, not personalized advice.