Your CV is read by robots, not humans

You spend over a week preparing, reviewing, and then perfecting your CV in order to apply for a job. A clean and clear format, strong achievements, and carefully chosen words that were pulled directly from a job description. You enter the website of the organisation seeking the resource in question, register, and then finally hit “Apply” feeling confident (having worked all week on the CV).

The outcome, within minutes (if not a day or so), is a rejection email. There was no interview. There was no follow-up, but just a polite message: “Dear XYZ, We regret to inform you..." Sounds familiar? Yes, this is the norm today adopted by many AI-ready organisations, where there is no human interaction at all. What really happened was that you (or whoever applied) were not rejected by a human or a recruiter per se, but by a machine (that is powered by AI).

This is no longer an unusual story. It’s becoming the default experience for job seekers around the world. Organisations today are flooded with applications. Sometimes hundreds (if not thousands) for a single role.

Reviewing each CV manually is no longer practical, so companies rely on artificial intelligence to filter, rank, and eliminate candidates almost instantly. These systems, known as Applicant Tracking Systems, scan CVs for keywords, qualifications, and patterns, deciding who moves forward and who doesn’t.

On paper, it sounds efficient and like an AI-ready badge that many organisations strive for. Faster hiring, lower costs, and more “objective” decisions. But the reality is more complicated. AI is only as fair as the data it learns from. If that data reflects past biases, the system doesn’t remove them—it in fact learns and scales them.

A well-known case involved Amazon, which had to abandon an AI hiring tool after discovering it favored male candidates. The system had learned from historical data where male candidates were more frequently hired—and simply repeated that pattern. This is the impact of not having humans as part of the process. Entirely relying on machines has a painful price to pay sometimes (especially if not given the ample time to assess).

The numbers behind this shift are striking. Research suggests that over 75% of resumes/CVs are rejected by AI before they ever reach a human recruiter. In large organisations receiving 200–250 applications per role, automation is no longer optional—it’s inevitable. But this efficiency comes at a cost. Highly qualified candidates can be filtered out simply because their CV doesn’t match the exact language or structure the algorithm expects.

This has created a new kind of job market where candidates are no longer writing for humans but for machines. Creativity is reduced. Personality is minimised. Everything becomes a game of optimisation. The difference between getting noticed or rejected can come down to a missing keyword or a formatting choice. And when rejection comes, it comes without explanation, leaving candidates unsure of what went wrong.

So what should students and future applicants do in a world like this? First, understand how the system works. Use keywords directly from job descriptions—don’t assume similar wording will be recognised. Keep your CV simple, structured, and easy to scan. Avoid overly creative designs that may confuse automated systems. Focus on measurable achievements, because numbers are easier for AI to interpret than vague descriptions.

But more importantly, don’t rely only on online applications. Because while AI may control the front door, humans are still inside. Networking, referrals, and building a strong professional presence can help you bypass automated filters entirely. In many cases, who you know—or who knows you—still matters just as much as what’s on your CV.

AI in hiring is not going away. It will continue to evolve and play an even bigger role in shaping careers. The responsibility lies with organisations to use it ethically and transparently. But as a candidate, you also have a role to play by adapting, understanding the system, and learning how to navigate it intelligently. Because today, you’re not just competing with other candidates.

You’re competing with how well a machine understands you before a human ever gets the chance. Until we catch up again next week, I urge you not to be disappointed (rather, look for real reasons) the next time you hear someone got rejected for a job. It could have been the doing of an AI.