According to LinkedIn, more than 900 million people use LinkedIn across 200 different countries and regions. Based on this, the fact that 93% of recruiters use LinkedIn to find applicants is not surprising. Recruiters would not pass a day without “LinkedIn search” being a part of their day-to-day tasks.

If you were to ruminate for a while, there may have been a point in time when a recruiter sifting through piles of resumes and CVs would have thought of an easier way to get access to qualified candidates. They may have imagined resumes categorised according to their qualifications, skills,  number of years, and so on. Then came LinkedIn and its miraculous set of filters, providing options to choose from. And candidate search has almost become synonymous with LinkedIn search. 

LinkedIn search seemed to be the best solution a recruiter could ask for. With more tools added to their repertoire for most segments of the market, hirers and job seekers have found a platform that makes life easier. However, with new solutions, new problems surface (and some of the old ones as well). The art of lying in resumes has taken on a new shape and form, and even with skill assessment and video assessment systems put into place, creative methods to bypass these have also developed over the years. This was immediately remedied by proctoring systems that evolved simultaneously. The point is, LinkedIn search and all the processes aligned with it have been constantly evolving.

But here’s a gap that affects parties on both sides of the equation, that is, the recruiters and the job seekers: Only 50% of LinkedIn members have a completed profile, despite the fact that 93% of recruiters use the site to locate prospects. Recruiters, although reliant on LinkedIn search, find that one of the biggest challenges is that their candidates' profiles are incomplete.

Candidates should update their LinkedIn profiles. In the highly competitive job market, the only way any recruiter can get an idea of how good a candidate can be is through LinkedIn profiles. Keeping the LinkedIn profiles up-to-date opens the possibilities for broader horizons. Although word-of-mouth, or in formal terms, “employee referral,” would seem to be the most impactful way to get the attention of hirers, being visible during the LinkedIn search phase and being added to the passive candidate pipeline helps open doors to possibilities that were not even thought about previously. 

LinkedIn has always been the bridge that connects hirers and candidates across the globe. And with AI in the picture, this gap can be bridged further. Of course, taking into account that we get candidates to complete their profiles as well.

Now, the obvious question would be, "Is AI going to take away jobs?”

Instead of blindsiding oneself by merely looking at this predicament from a “yes/no” perspective. A view across the landscape would give a better perception and, hence, eliminate the fear induced by AI. 

According to this LinkedIn article, the average time to build the hiring process can typically take a month to six weeks, considering that everything goes perfectly as planned and that the hiring process doesn't take too long. To build a talent pipeline as well, the period could easily be applied. 

Right off the bat, for recruiters, one of the disadvantages that could be addressed is the removal of recency bias. A form of bias where humans tend to take into consideration only the most recent sources of information they process to come up with conclusions. The problem with this mode of thinking, especially when it comes to picking the right candidates from a large set, is that many tend to ignore potential candidates that may have been better for the role. Rest assured, although you may have picked a ‘good candidate’ , picking the best of the lot is not achieved. As seasoned recruiters would agree, a single candidate could change the course of your business for better or worse. 

If we zoom in and take a few other factors like human errors, repetitive tasks, and other aspects into consideration, that’s adding on to other factors that add to the hirer’s bandwidth.  It could be safe to assume that a large amount of time, money, and workforce is spent on these tasks rather than the actual task. That’s where AI comes into the picture, catering to the aspects of human error and redundancy. AI upgrades a recruiter to a “10X recruiter” by adding to the bandwidth, opening the possibility to create up to ten talent pipelines within the timeframe where only one was possible. 

Changing human nature is not easy, and in many cases, it can’t be helped. However, what if there was a way to put the best candidates in the hands of a recruiter who could pick the candidates in a single sitting, rather than letting them go through different piles of CVs of candidates ranging from excellent to not-so-good candidates? There’s not much suspense pertaining to the tool, as AI would be the best option to get the job done. Being a language model, ChatGPT has the ability to process the results of candidates, which are in the form of typed text, and the data can be derived not only from the skills assessment tests but also from resumes and CVs in no time. 

I myself have had the opportunity to experiment with the prowess of ChatGPT. We were able to create hyper-personalised messages during the candidate outreach phase. The results are rather stellar. Instead of spending hours looking through candidate profiles and creating personal messages for potential leads, ChatGPT does the hyper-personalisation for you, and it works like a charm. It also has filters that ensure that the LinkedIn search process is optimised more for the recruiter’s needs.

The fear of automation taking away jobs is a “horror story” retold across the ages. Will the job market change? Yes, it will, but it is definitely for the better as humans get the opportunity to seek and execute tasks that are more meaningful, and they get the opportunity to allocate their efforts to bigger and more relevant decisions. In simpler terms, the place of humans, in the long run, would be to move towards a hybrid work setting where the shortcomings of AI are rectified by humans and vice-versa.