Are you someone that has applied for hundreds of jobs/roles with nothing at the end of it? Spent a lot of time researching the company, have written countless personalised cover letters to accompany your CV? Perhaps it’s weeks since your application and you have not received anything back in return – regardless of how qualified you are? If that is the case, then it may well be recruiting software systems that are sifting your CV out of the process. If this is the case has the recruiting process has lost the human touch? Is there an overreliance on poorly programmed software systems that sift out great candidates (like you) due to a lack of a recruiters eye joining the dots of your application? This article will look into recruiting software systems at work that will be removing good candidates from the recruiting process. We will offer valuable insights and more to the point what to do about it if you are experiencing the pain of rejection at the hands of recruiting software systems

Automated Recruiting Tools

Recruiting practices can be convoluted, impenetrable and have become far too reliant on algorithms. “Artificial intelligence” powered recruiting software scans CV’s & covering letters for keywords and role-specific criteria. As a result, and if you are not playing the A.I. recruiting game, the algorithm will be unable to find your CV. The software will be filtering out your CV out regardless of fit. Sadly putting it in the unlucky candidate’s pile.

Now I do realise of course that the mere mention of the acronym A.I. will create controversy. However, this is to draw attention toward the pre-configured automated recruiting tools and their inherent inflexibly. For example, an Applicant Tracking System (ATS) is a workflow-oriented tool that helps organisations manage and track the pipeline of applicants in each step of the recruiting process.

In addition, a Recruiting Management or Marketing System (RMS) complements the ATS and supports recruiters in all activities related to marketing jobs, sourcing key staff and creating a pool of available talent. Thus, automating much of the recruiting process such as candidate scoring and interview scheduling. These systems now represent the bulk of the CV sifting and recruiting process in many organisations.

“In fact, more than 90% of employers in our survey use their RMS to initially filter or rank potential middle-skills (94%) and high-skills (92%) candidates.”  (Harvard Business School – 2021)

Recruiting Systems

These systems have by and large become an integral part of the recruiting process. However, first and foremost they are designed to maximise the efficiency of the process for the recruiter. That leads them to focus on candidates by using very specific parameters. This is to minimise the number of people that can be actively considered. The Harvard Business School Project suggests that –

“For example, most use proxies (such as a degree or possession of precisely described skills) for attributes such as skills, work ethic, and self-efficacy. Most also use a failure to meet certain criteria (such as a gap in full-time employment) as a basis for excluding a candidate from consideration irrespective of their other qualifications. 

As a result, they exclude from consideration viable candidates whose resumes do not match the criteria but who could perform at a high level with training. A large majority (88%) of employers agree, telling us that qualified high-skills candidates are vetted out of the process because they do not match the exact criteria established by the job description. That number rose to 94% in the case of middle-skills workers.”  (Harvard Business School – 2021)

Recruiting Technology & candidate interface

Clearly, technology has made it much easier for employers to post jobs via job sites such as LinkedIn, Indeed & Monster. However, making it easier for the employer, doesn’t necessarily make it easier for the job seeker. You may well not be getting rejected for the role you feel amply qualified for, you are just not getting past the technology.

Moreover, in some cases what the software is scanning for doesn’t make much intuitive sense. For example, the algorithm will look for someone who also knows about “computer programming” when what the role really needs is data entry. This makes crafting a CV and supporting people who would be a good fit invisible to the employer and recruiting process.

Is the technology working for candidates?

Recruiters then are seemingly leaning heavily on the technology to sift out candidates, probably due to the sheer number of submissions. Whereas they may need to be more creative in terms of how they consider applications and what types of people could be the right fit. Moreover, the recruiting process seems to have lost the human touch. The ability for human intervention and to see & feel the potential in a person and CV. Rather than the lack of A.I. correct language. We have to be aware that applicants think their CV is being written for another human being when clearly they are not.

This style does not seem to fit with what the system is trawling for. So logically we have the distinct possibility for a disconnect, quite literally because of the choice of words. Thus making things very difficult for the candidate to aim their CV correctly. To add to the confusion, many companies have the tendency to add to job descriptions rather than subtract from them. Meaning job requirements have ballooned beyond the candidate’s ability to actually meet them.

Tips to make your CV hit the A.I. mark

Enough of the problems then, let’s focus on what we can do to give you a better chance of your CV ending up in the lucky pile of candidates.

  • Make sure your CV, cover letter, and application match the job description. That may well mean using the same phrasing to cover the job/person specification main points, even if that can feel a little disingenuous and false. This is very succinctly put by Harvard management professor Joseph Fuller put it, “Being robotic is good if you’re talking to a robot.” 
  • Check out LinkedIn (other job platforms are available) to see what skills and qualifications people have in the job you want to apply for. Make sure you list them if you have them, or make a point to get them if you don’t. Perhaps it’s not wise then to waste your time applying for a job you are highly unlikely to get an interview for. Not good for your confidence or self-esteem in the end. Try to be focused and think about why you are applying for the role and what you have to offer.
  • Try not to leave unexplained gaps in your CV. If you took a year off for child care, illness or going back to university then say so. Tell the recruiter what you did during the Covid lockdown if it will showcase further/professional development. Perhaps you volunteered to help a cause you feel passionate about? Otherwise, it will look like you were doing nothing at all, as a result, you might be screened out by the algorithm

Job descriptions & job search

So in the end what can we do to help those that are navigating the job market to give them the best chance for the CV to end up in the lucky candidate pile? Clearly, job descriptions change, thus making those that have been out of work for a while at a disadvantage. Mainly due to the algorithms adopting different search criteria for the role. Therefore having a clear job search strategy is going to help you be more specific with the roles that will fit your career capital. Making it very clear to the recruiter & the algorithm how you fit both the system and the company. Utilising the language of the person & job specification will by and large help the algorithm see you and how you measure up to the criteria for selection.


For many candidates, the entire recruiting process can feel like an impenetrable black box. Job seekers are expected to come onto the job ready-made. All with the knowledge, experience, skills, and everything needed for the job and to hit the ground running. However, as we all know very few people do or fit the job exactly.

An attempt to make the recruiting process more efficient has rendered it to a large extent inefficient. As a result, the candidates who are a great fit for the majority of the role, are screened out because they are not a 100% perfect fit. The flip side of course is that recruiters can be so inundated with CV’s online that they only look at the first few. Thus hiring the people they can get the fastest instead of the people who are the best fit. Therefore the great candidates getting sifted out. No easy answers to the problem, though the conclusions are, I am sure, somewhere in the middle.

So if you are getting knocked back and not receiving replies for your application then do what professor Joseph Fuller suggests, think like a robot and craft a CV to get noticed by both the human and the algorithm.


Bibliography & References

*Fuller, J., Raman, M., Sage-Gavin, E., Hines, K., et al. 2021. Hidden Workers: Untapped Talent. Published by Harvard Business School Project on Managing the Future of Work and Accenture. (accessed 24/09/2021)


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