AI Has Entered the Job Application. Recruiters Say It's Changing What a "Good CV" Even Means
Job hunting has quietly become a game of AI versus AI — and recruiters are the ones caught in the middle.
On one side, applicants are feeding their work history into AI tools to produce sharper, faster, more tailored CVs for every role they apply for. On the other, employers are using their own AI systems to filter, rank and shortlist the flood of applications coming in. The result, according to recruitment professionals, is a hiring landscape that looks efficient on paper but is becoming harder than ever to navigate in practice.
The Numbers Behind the Shift
New data from global recruitment firm Michael Page puts a figure on what many in the industry have suspected for a while: in its 2026 Talent Trends report, based on responses from over 60,000 professionals worldwide, roughly two in three job seekers said they now use artificial intelligence to refine their CV's wording, tailor it to specific roles, and condense their skills into recruiter-friendly summaries.
IT professional Brodie Shane is one of them. He maintains a detailed record of his career achievements and lets AI reshape it for each application — a habit shaped partly by having worked on the recruiting side himself and seen firsthand how heavily some employers lean on keyword-matching software. His approach, he says, is to prompt carefully enough that the AI stays factual and doesn't invent experience he doesn't have.
For Shane, the fact that both sides of the hiring equation are now running AI in parallel is more reassuring than worrying — it simply speeds things up without changing what's true about his background.
When Every CV Starts to Look the Same
Not everyone shares that confidence. David George, senior managing director at Michael Page, says the sheer scale of AI-assisted applications is making it genuinely tough for hiring teams to tell strong candidates apart from average ones — because on paper, they've started to blur together. He describes the old benchmarks for judging a "good" versus "average" CV as losing relevance altogether, with more weight now shifting to soft skills and to the interview stage, where a candidate has to make their case in person rather than on the page.
Still, George isn't arguing against using AI in job applications — quite the opposite. He believes skipping it at this point would put a candidate at a real disadvantage. His caution is more specific: AI can polish language, but it can't manufacture genuine accomplishment. That part, he says, still has to come from the applicant telling their own story.
The Risk of Filtering Too Aggressively
The employer side of the equation carries its own risks, according to recruitment consultant Meqa Smith, who is based in Brisbane. She encourages the businesses she works with to be far more deliberate about how they write job ads and structure application requirements, precisely to reduce the volume of generic, AI-generated submissions landing in their inbox. One practical tactic she recommends is building a short video response into the application process — a low-effort filter that tends to separate genuinely interested candidates from those applying indiscriminately. Doing this, she argues, buys recruiters back the time they need to actually engage with the applicants who make it through.
George raises a related concern from the employer's side: lean too heavily on AI too early — chatbots screening candidates before a human ever gets involved, for instance — and businesses risk turning off exactly the people they most want to hire. A clunky, impersonal early-stage experience, he warns, can cost a company its next standout employee before that person ever gets the chance to interview.
Why Scaling Back on AI Isn't Realistic
University of Queensland data science professor Gianluca Demartini frames the current state of recruitment bluntly: it's become a contest between applicants and employers, each side using AI to try to outmaneuver the other for efficiency's sake. He points out two distinct costs to this arms race. On the applicant side, individuality is getting flattened, since AI tools tend to converge on similar phrasing and structure. On the employer side, the risk is more serious — AI-driven screening can end up filtering candidates based on factors like race or gender that have nothing to do with whether they're right for the job, often without anyone intending it.
Despite these concerns, Demartini doesn't think the solution is to use AI less. He sees real, tangible efficiency gains from these tools and argues the smarter path is using them with more scepticism — and making sure a human stays accountable for any decision an AI tool makes or recommends.
The Piece Missing From This Conversation
Taken together, these perspectives point to the same underlying issue from different angles: AI has made hiring faster, but it has also made the paperwork behind it far less reliable as a signal of who someone actually is. A resume was never a verified document — it was always a claim. AI has simply made that claim easier to produce at scale, on both sides of the desk.
That's the gap Talent Tabloid was built to talk about. We believe the next stage of hiring isn't about using less AI — it's about pairing AI-accelerated hiring with verified digital identity, so that speed and trust aren't working against each other. If recruiters are right that CVs "all look the same" now, the fix isn't a smarter filter for words on a page — it's a reliable way to confirm the person behind them.
Source: ABC News, "CVs losing value for hiring as use of artificial intelligence changes industry, recruiters say," by Emma Johnson, 22 May 2026.
