The impact of AI on applying for your first job

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If there’s any universal truth about AI, it’s that it will dramatically impact almost every facet of business, even when it comes to those looking from the outside in: job-seekers.

The impact of AI on the job application process is becoming more and more important as organisations rely on technology in their hiring process. Fewer resumes appear in front of a real person - it’s AI who is calling the shots when it comes to collecting, reviewing, and considering applicants.

We are beyond imagining AI’s potential in better matching job-seekers to open positions - this is happening as we speak. One recent study showed 491 out of 500, or 98.2 per cent, of Fortune 500 companies use some form of applicant tracking system (ATS). Many online job boards do the same.

University students should pay attention to the emerging technologies affecting job application processes, as they could be commonplace by the time they apply for jobs after graduating. If anything, automated screenings are an opportunity for first-timers to avoid potential human biases which otherwise might have favoured more experienced candidates.

Modern candidates will more likely make it past the AI layer if they understand how the underlying technology acts – so read on to get ahead of the pack!

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Applying for AI

The main use for AI in job application currently, is resume filtering. AI-powered programs use different algorithms to scan and filter resumes, then assign scores to candidates - all in real-time. By default, that means a lot of resumes aren’t seen by human eyes. In doing so, AI does a lot of things to form a decision on whose resume matches the organisation’s needs.

These programs filter by analysing skills and experience to align with the requirements of the position in question. To a certain extent, including keywords in your resume will help you score with these programs, however the systems have evolved and become more intelligent, matching phrases, entire sentences, and even paragraphs.

Some tools analyse job descriptions and use an existing employee, typically a top-performing one, as a basis for comparison and meaningful ranking. Others use interactive elements such as automated video interviews, questionnaires or games to gauge certain skills. This is especially common when an organisation wants a candidate with skills like critical thinking, problem solving, creativity, and communication skills.

Creating a talent pool

Furthermore, AI’s impact in hiring can also help to build a talent pipeline. After all, most companies are sitting on a treasure trove of resumes from candidates who previously applied but weren't hired.

In fact, you don’t even have to apply for the job to be considered by some companies. The so-called passive job search process is a popular method of using technology to find qualified candidate information through well-kept profiles on professional networking and career-focused sites like LinkedIn, AngelList, Hired, and others.

For first-time job seekers, AI can be the gateway to discovering an ideal job and to securing it. Some businesses have an open-door policy, allowing candidates to add their resumes even if there aren’t any open positions available. Both sides profit: an organisation collects information on those showing interest in working there while candidates get to be in consideration for a future job, regardless of whether they actively apply for it.

Being strategic is key

Effective hiring is achieved with the right processes, mixed with the right technology. The same can be said for job hunting and applying. With technology advancing inch by inch each day, graduates seeking their first job must practise proper job search and application techniques along with the required skills and knowledge.

In order to give yourself the best chance at getting your resume seen, it’s mandatory to know how AI is scanning your application and apply various tricks regarding keywords, formatting, and virtual interaction.

Those familiar with optimising their resumes and applications for the technology can be elevated or at least get a baseline of what exactly they are facing. The algorithms aren’t perfect, but they are here to stay and there’s no changing that.

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About the author

Dr. Jeremy Nunn

Dr Jeremy Nunn is Founder and Director of technology company Workmetrics. Dr. Nunn is a Murdoch alumnus, having completed his Doctorate of IT, Master of Science and Bachelor of Science at Murdoch University.

Posted on:

12 Sep 2019



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