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Guest Blog – 5 Ways AI Is Bound To Leave Its Impact On HR And Recruiting

Adrian Dixon

July 31, 2019

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Technology is dramatically transforming the way businesses operate and function. All departments within the organization are at the receiving end of a technological overhaul and HR is no exception today. 

One technology, in particular, that is making huge strides and is bound to have the biggest and long-lasting impact in HR and a core part of recruiting trends for the next few years, is Artificial Intelligence and Machine Learning.

What is machine learning?

Machine learning is a subset of Artificial Intelligence that deals with deep learning algorithms and predictive analytics. It is an innovative technology that focuses on systematic analysis of data that gives computers the ability to autonomously learn without being specifically programmed for the same.  

The computer relies on patterns and inferences instead of explicit instructions. The systems learn from data, identify patterns and use them to make data-driven decisions with minimal human intervention. 

Machine learning in HR and recruiting

The hiring scenario is becoming increasingly competitive, especially in the tech field. With the work culture making a move towards gig economy, retaining existing employees and recruiting tech talent to fill organizational roles is a resource-intensive activity. 

Use of machine learning algorithms can reduce the load on HR personnel, streamline the recruitment process, remove the repetitive tasks and infuse efficiency in HR. Here is how machine learning is impacting HR and recruiting.

1. Attracting top talent

Whether you are hiring for startups or enterprise level businesses, the importance of sourcing top talent and hiring them cannot be undermined. Machine learning applications are being used by a large number of companies in order to improve their chances of attracting top talent. 

Manually writing and posting job adverts does not guarantee optimal results. Machine learning algorithms can be used to analyze the language patterns in the job postings which can help determine the important do’s and don’ts of the process and can even help phrase the adverts so that they are more effective in attracting talent.

Artificial Intelligence and Machine Learning solutions are already being used by portals such as LinkedIn and Glassdoor in order to narrow down the search to the right candidates. Using advanced algorithms, it is possible for the job portals to shortlist the candidates, filter them on the basis of set criteria and narrow down the pool of talent. 

Based on the user’s data from previous searches and interaction maps derived from click history, the platforms help recruiters connect with the appropriate talent without having to jump through multiple loops. 

2. Bias-Free hiring

No matter how objective HR tries to be during the recruitment process, unconscious bias tends to creep into it. Intentionally or unintentionally, human recruiters can end up discriminating against certain candidates on the basis of their age, race, gender or other demographic characteristics. 

Use of AI-powered applicant tracking system eliminates the need for the recruiter to go through thousands of resumes in order to shortlist the candidates while simultaneously reducing the chance for biased hiring.

Machine learning algorithms that are trained on clean datasets level the playing field and reduce bias from the hiring process. Automation of the applicant and resume screening process also reduces the hours that recruiters spend on analyzing and going through the candidate profiles individually to shortlist them manually. It also shortens the time to hire by significantly speeding up the hiring cycle. 

Ideal’s resume screening software is one of the best examples of such advanced tools which are meant to streamline the tedious hiring process. The platform ensures that talent is evaluated objectively. Also, it ensures that each and every applicant is reviewed and treated fairly.

3. Skilled workforce

In order to form an engaged workforce, training and development activities are a necessary part of the employee retention strategy. In a rapidly changing environment which witnesses new technological innovations taking place quickly, continuous learning has become a must and needs to be facilitated from the onboarding stage itself. 

Employees within the organization have access to a large pool of learning resources but they often fail to identify and shortlist the training or program that has the potential to be most beneficial for them. 

Machine learning can give personalized recommendations that result in optimal matching of the resources with the training and development programmes, resulting in a highly skilled workforce.  

4. Employee retention

Personalization is increasingly becoming an important part of attracting, hiring and retaining top talent. AI-driven hiring software works on the principles of ML which help HR professionals realize the unique needs of individual employees and assist them in formulating personalized engagement programs for each of them. 

By using natural language processing, another artificial intelligence subset, AI can convert a large amount of unstructured data into structured data which can then be analysed by machine learning algorithms to result in actionable inferences.

In order to improve employee retention, HR professionals can make use of ML algorithms to formulate personalized rewards, recognition and incentives programs which boost employee engagement and make their contributions feel more noteworthy. 

5. Building a talent pipeline

Understanding the motivations behind an employee deciding to stay at a job or leave is one of the most crucial aspects of HR that needs to be analysed. Employee attrition is a big risk to any organization. The company incurs significant expenses every time an employee resigns and needs to be replaced. 

Utilizing the employee data collected from IoT devices such as smartbands, companies can make data-backed decisions, identify roles that are at a higher risk of attrition and plan building of a talent pipeline accordingly. ML algorithms can help recruiters predict future hiring needs, identify possible issues within the company process and take measures to rectify the same.

Closing words

While machine learning may sound like a magic wand to eliminate all HR related woes, it has its own set of drawbacks as well. The statistical models and algorithms that form the backbone of ML are completely linked to the data it is trained on.

The true potential of machine learning and artificial intelligence in the field of HR is just beginning to be explored. Despite the challenges, the potential that this technology has is immense and it promises to have a transformational impact on the way HR processes are managed within organizations, both large and small. 

Vinati Kamani writes about emerging technology and their applications across industries for Arkenea. She is an avid reader and self-proclaimed bibliophile. When not at her desk penning down articles or reading up on the recent trends, she can be found traveling to remote places and soaking up different cultural experiences.