The human touch still matters in hiring

The right candidate might be hiding just behind the algorithm, writes Matthew Munson.

In today’s job market, your résumé’s first reviewer probably isn’t human. Before it reaches a recruiter or hiring manager, it’s likely scanned by software called an Applicant Tracking System (ATS) – designed to read, interpret, and categorise thousands of résumés in seconds.

That’s efficient, but not always effective. When parsing goes wrong, strong candidates can vanish from the shortlist. Add to that the rise of generative AI helping jobseekers polish their applications, and we’ve entered a hiring landscape where both sides are optimising for speed, and the results are often less than ideal.

What résumé parsing is (and why it matters)

Parsing is how an ATS converts a résumé into searchable data fields like name, title, dates, skills, and education. If your formatting or structure confuses the parser, key details can be lost or misread. In other words: you might be the perfect fit for the role, but the software doesn’t see it.

There are three main parsing methods in use today:

• Keyword-based: Looks for standard section headers and familiar formats. Stray too far from convention, and it breaks.
• AI/NLP-based: Uses natural language processing to infer context and extract meaning – but it’s not foolproof.
• OCR-based: Kicks in when résumés are uploaded as PDFs or images. Accuracy often drops sharply here.

A well-structured résumé must appeal to both an ATS and the person reading it later. Keep it clean and clear:

• Use universal fonts like Times New Roman, Calibri, or Arial (12pt).
• Avoid fancy designs – columns, tables, text boxes, or graphics can scramble your data.
• Stick to clear headers like Experience, Education, Certifications, and Skills.
• Incorporate relevant keywords naturally – think of your résumé as SEO for your career.
• Save and upload in .docx, not PDF; OCR parsing on PDFs often misreads your content.

As JP Browne, practice manager at Talent Auckland, puts it:

“Some organisations are moving away from AI screening tools because applicants can use AI to generate great cover letters that don’t match their CVs. If the substance isn’t there, it’s game over. Don’t assume your job title tells the story – spell it out.”

As a hiring leader, I’ve seen firsthand how technology can both help and hinder recruitment. ATS tools allow us to handle enormous applicant volumes – sometimes 750 to 1,500 per role in our Sydney office alone. That’s a staggering number, and while automation helps manage it, it also creates distance between recruiters and talent.

Responding personally to that volume is almost impossible, and that’s where candidate experience begins to suffer. It’s one of the biggest frustrations in the market right now: both employers and jobseekers feeling unseen.

Keeping humans in the loop

ATS tools are useful, but they can’t replace human judgement. We recommend keeping a hiring professional involved in the screening and selection process that creates the final shortlist. With the use of AI, the only way to be sure of a candidate’s suitability is to speak to them.

Take a second look at “near miss” candidates whose résumés may not have been perfectly formatted but show potential, and revisit your role briefs and consider re-advertising with clarified requirements or alternate job titles.

Most importantly, ensure interviews are being used to assess capability, not just alignment to the AI-generated CV.

Final thoughts

For jobseekers: Keep your formatting simple, your language clear, and your story authentic. AI can assist, but your personal substance needs to shine through.

For employers: Use automation to streamline, not to decide. Revisit your ATS settings, refine your job ads, and ensure a recruiter still reviews the shortlist. Because at the end of the day, the right candidate might be hiding just behind the algorithm.

Matthew Munson is the managing director at Talent.