The Way Machine Learning is Being Used for Hiring

The Way Machine Learning is Being Used for Hiring

You only have to look down at your smartphone to recognise the impact technology has had on the way people apply for jobs. Rather than scanning the local newspaper for vacancies many will either use a dedicated app or even browse social media.

However, it’s not only the way candidates apply for roles that has evolved, as more and more companies are making use of the benefits machine learning is able to offer its business when it comes to making the right decision when it comes to its hiring process.

Although the way machine learning is used can differ depending on the sector and the way the information is used, it primarily falls in the following categories:

Talent Recruitment

While human interaction will always be needed at some point in the recruitment process, there can be more laborious tasks that can eat into a company’s time when trying to find the perfect candidate. Although we can make the conditions of the job application clear, this won’t stop some people trying their luck.

Fortunately, the use of machine learning can be used to take charge of the more cumbersome and time-consuming task, such as application reviews, thus leaving your business with more time to focus on the finer details.

Talent Sourcing

Many companies know that the perfect candidate is out there, but they may not be aware of the opportunities available to them, especially in such a saturated market.

Rather than hope the perfect candidate makes an application for the role, the use of machine learning can ensure that the business is put in touch with the right candidate, regardless of whether they’ve applied for the role in question or not.

Many recruitment companies make use a virtual assistant that can pick up the slack, leaving the agency to concentrate on more pressing issues. One of the tasks that a virtual assistant is able to undertake is using client credentials to connect with third-party candidate websites, and highlight prospective candidates using a pre-determined algorithm.

Candidate Screening and Engagement 

The recruitment process a company has in place can differ and depend on several factors. Some roles may require for a complete background check, whereas others may need to check references.

Regardless of the role being applied for, there’s no denying that the process can be hindered by endless phone calls and emails relating to the role. Of course, the candidates making these enquiries are doing nothing wrong, but it does showcase how a simple recruitment drive can become a complex endeavour when trying to maintain engagement with prospective candidates.

Although it would be easy to assume that not communicating in any regard would be the way to move forward, this can come with its own set of complexities. For example, there will be times when a business has to contact a candidate with a request for information, and this can only be done if there are contact details in place.

However, this doesn’t mean that a company must suffer in silence, as long as it’s willing to embrace the benefits machine learning has to offer.

One example of machine learning is its use by businesses and recruitment agencies  to respond to candidate enquiries using natural language processing.

Natural language processing is essentially an artificial intelligence that can offer responses to real-time enquiries using the analysis and synthesis of natural speech.

This is especially useful if you find that the company spends a lot of time dealing with a lot of the same queries.

It’s not only questions from candidates that machine learning is able to take care off, it can also aid businesses when it comes to scheduling interviews.

Another time-consuming process can be trying to find the perfect time for an interview, especially if the candidate is already employed.

One example of this can be the AI-powered assistant known as Amy. This product scans the emails of candidates, and work with them to find the ideal time for an interview.

This type of technology isn’t limited to just arranging job interviews, it can also be used to stay on top of any potential sales leads.

The Real Benefit of Machine Learning Within the Recruitment Sector

Although it’s evident that machine learning can get rid of a lot of the more time-consuming tasks, the benefit is much more than that.

Because those in charge of the hiring process will be spending less time on the reviewing of CVs, replying to candidate’s questions and sourcing new talent, they will be left to fine-tune the process to ensure that successful candidates are introduced into the company seamlessly. It can also help reduce expense moving forward, as the company will be able to source candidates in a completely different way, without having to spend many hours perusing talent pools.

Can Machine Learning Benefit my Business?

If you’re a trader or start-up, you will probably be dealing with a lot of the communications yourself, and as such, machine learning probably isn’t required at this point. However, as a business scales up, it’s likely that the communications being received by job applicants will become more overwhelming. The use of machine learning can help lower the manpower needed, and really bring a benefit to the company when it comes to simplifying its recruitment process.

It’s worth noting that machine learning isn’t limited to the recruitment sector solely, and it can be used in several different ways, including staying on top of sales leads and finding potential partnership opportunities.

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