In 2023 this page asked whether you should let ChatGPT write your resume. The question is now settled, though not in the way most career advice predicted. The problem is no longer that a machine wrote your resume. It is that a machine is reading it, and that roughly three in four of the people you are competing against used the same tool you did.
The finding that inverts the old advice
In June 2026, researchers at the University of Maryland’s Robert H. Smith School of Business ran more than 2,200 resumes through several leading large language models. When a model compared an AI-written resume against a human-written one of equivalent quality, it preferred the AI-written version between 67 and 82 per cent of the time. Candidates whose materials came from the same model the employer used for screening were 23 to 60 per cent more likely to be shortlisted than equally qualified candidates who wrote their own.
That is worth reading twice, because it overturns a decade of advice. At the screening layer, AI-written text is not a liability. It is an advantage.
Two things stop that being a strategy. You do not know which model sits behind a given employer’s screening, so you cannot aim at it. And the researchers were not celebrating the effect — they were documenting a bias, and they showed it can be cut by more than half with better prompting on the employer’s side. The advantage is real today and is being engineered away as you read this.
What happens after you clear the filter
Robert Half surveyed more than 2,000 hiring managers in November 2025 and published the results in March 2026. Sixty-seven per cent said reviewing AI-generated applications had slowed their hiring; one in five reported delays of more than a fortnight. Sixty-five per cent said the surge had made it harder to verify what candidates could actually do. Eighty-four per cent reported heavier workloads.
Their response is the part that matters to you. Forty-two per cent are spending longer on each application. Thirty-eight per cent have added interview rounds. Thirty-two per cent have rewritten their job advertisements specifically to defeat generic AI answers.
So the resume that sails through the filter now delivers you into a process redesigned to work out whether you are real. Getting shortlisted on fluent text you cannot substantiate is not a win. It is a longer and more public way to lose.
Where AI genuinely helps
The best evidence for AI assistance is also the least glamorous. MIT Sloan researchers Emma van Inwegen, Zanele Munyikwa and John Horton studied 480,948 job seekers on an online labour marketplace, randomly giving half of them algorithmic writing assistance. Those who received it were 8 per cent more likely to be hired, received 7.8 per cent more offers and earned 8.4 per cent more.
Read the mechanism before you read the headline. The assistance was spelling, grammar, punctuation and style — proofreading, not authorship — and the underlying data is from 2021. Applicants whose resumes were less than 90 per cent correctly spelled had a 3 per cent hiring rate in their first month. Those above 99 per cent were hired nearly three times as often.
The lesson generalises. AI is very good at removing what is wrong with your resume. It is very poor at supplying what is missing.
Four things it still gets wrong at executive level
1. It does not know your numbers
A model will write that you significantly improved operational efficiency. Only you know it was fourteen million dollars of cost out over eighteen months across four sites, while holding safety performance. The first sentence is available to everyone. The second is available to you alone, and it is the only one a chair will remember.
2. It writes to the middle
A language model is an averaging machine trained on millions of documents, most of them ordinary. Averaging is precisely the wrong instinct at general manager level and above, where you are being assessed on judgement and on what makes you different from three other credible people.
3. It cannot read the room
The same career, presented to an ASX-listed board, a founder-led business, a government department and a not-for-profit, needs four different emphases. A model has no idea which one it is writing for unless you tell it, and most people do not. We have written elsewhere on how Australian resumes differ and on how executive recruiters actually read them.
4. It invents
Models embellish scope, and they do it plausibly. At executive level a claim you cannot defend in the room is far more expensive than a modest one you can. Reference checks at this level are conversations between people who know each other.
A division of labour that works
Give the model the mechanical work: structure, tightening, grammar, and producing tailored variants once the substance is settled. It is also a useful interrogator — ask it to put twenty questions to you about the role, the kind a chair would ask, and answer them out loud. You will recover material you had forgotten.
Keep for yourself the things it cannot source: the numbers, the decision about which three achievements carry the document, the judgement about what to leave out, and the final read.
One test settles most arguments. If a paragraph could appear on somebody else’s resume without alteration, it is not doing any work.
The Australian layer
Jobs and Skills Australia has warned that AI screening built around keywords and formal qualifications routinely misses what its Deputy Commissioner, Megan Lilly, calls invisible skills — judgement, de-escalation, cultural competence — and that talent goes unrecognised when a resume does not happen to use the matching terminology. A National Skills Taxonomy is being trialled to give the market a common vocabulary, with rollout from the middle of 2026.
Hays data cited in the same analysis puts the tension plainly: 85 per cent of hiring managers report skills gaps and 86 per cent are moving to skills-based hiring, but only 64 per cent say skills-based hiring is meeting their expectations.
The practical consequence for an Australian executive is unglamorous. Name your capabilities in the language the market uses rather than in your employer’s internal titles, because both the machine and the taxonomy behind it are matching on words.
What we would do
Use AI to check and compress. Do not use it to decide what your career means. The screening layer currently rewards machine-fluent prose, but that edge is temporary, unaimable, and it hands you nothing once a human starts asking questions — and in 2026 more humans are asking more questions than at any point since the resume was invented.
You can do all of this yourself. What you cannot do is read your own document the way a stranger will. If you want that read done properly — marked up by a consultant, with a report card and an ATS test:
$75.00 inc. GSTAdd to cart
Sources: University of Maryland Robert H. Smith School of Business, 22 June 2026; Robert Half hiring managers survey, fielded November 2025 and published 10 March 2026; MIT Sloan, Algorithmic Writing Assistance on Jobseekers’ Resumes Increases Hires; Jobs and Skills Australia. Candidate adoption and application-volume figures from HireVue’s 2026 report and LinkedIn data, as reported by Forbes on 17 July 2026. Most recent source consulted: 17 July 2026.
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