‘Data Science and AI’ -presently the hottest topic around the globe. While not a single domain is now free from the paw of a booming data science giant, human resource management (HRM) has been its last target. So How you start your Data science career?

But the expansion of data science and AI application in HRM has been so rapid that most MNC’s, even SMEs, implemented the application of AI and ML within their HR division. 

Amongst all of the application, analytics has already become the topmost priorities of global HRM. Data science is becoming the top favorites for most of the HRM functions. Let’s dig out how data science is building up the future for human resource and management?

What are the Scopes of Artificial Intelligence in HR?

Before answering this question, let’s look at the three key strategic goals of present-day HR functions. It’s as follows.

  • Landing with best-fit data-driven decisions
  • Lower the functional cost of HRM with intelligent automations
  • Enhancement of Employment experience
  1. Landing with best-fit data-driven decisions

Any kind of business decision is highly dependent on data. With the increasing number of available real-time, manual analysis of real-time data is now a real challenge for HR professionals. On-time insight drawing is the key to successful and sustainable decision making. 

The time required for the manual effort of data analytics makes the insight generation delayed, ultimately making the business decision out of date.    

AI-driven data analysis provides real-time insight generation as well as corresponding recommendations. So the business decision taken by HR is now becoming competitive and sustainable.

Besides, HR decisions driven by artificial intelligence have always remain unbiased and inconsistent,  making the HR function more beneficial to Human Capital Management. With the help of data science and AI, unlike others, the HR teams are now eligible to provide faster, unbiased, scalable, data-informed services. 

2. Lower the functional cost of HRM with intelligent automations

At Least Once in a life, we all have felt irritated with our HR.  Yes, it’s true providing timely replies to the employees’ specific queries, generating an on-time vendor invoice, monthly payslips, personalities employee benefits tracking, and management. Everything becomes messy, mainly for large companies. After all, you have to admit the fact that human intelligence has limitations. So, staffing in HR becomes an option, but that’s not the cost-effective business decision. 

Here comes the need for AI. With advanced machine learning algorithms, all of the above tasks can be made automated. These days you get all the payslips, tax-related forms, and personalized employee benefits on time. 

Automation is also a good option for processing repetitive HR tasks leading to greater productivity and excellent proficiency. 

3. Enhancement of Employee experience

Here you can think about customer experience. The faster the solutions, the happier are the customers. The same is applicable for employees. The recruitment process, methods of onboarding, planning, and implementation of performance-based appraisals affect the employee experience to a greater extent. Even the experience of one employee leads to the expectations and views of future employees too via professional networking. 

So HRM must provide their employees with an adequately smooth and positive experience.

Besides, employees are always happy to stay engaged and valued by the company.  

With the help of AI, employers can now monitor the real-time morale, performance, and productivity of their employees. The ML algorithms used in the dedicated AI application can track and analyze business communication, daily productivity, exceptional performance on its own.  

Application of AI into the employee life cycles makes recruiting, onboarding, candidates background verification, etc., smooth and fast. Above all, the entire HR process dedicated to employee experience becomes cost-effective.

These three are the three broad scopes of data science and AI in HRM now. Let’s dive into a narrower division. 

Application of Artificial Intelligence in Workforce Management 

  1. AI-based recruitment

Recruiting is no more simple than Shortlisting 5 profiles from 100 submitted applications and calling them for an interview, followed by selecting 1 or 2 from those shortlisted candidates. With digitization of the recruitment process and the job search behaviour of candidates, an HR professional of an MNC’s has to go through an average of 10,000 profiles of prospective candidates. 

Some might say we can still stick to a data-driven fixed numbered application approach, but that proves to be a disappointing talent management strategy in the present competitive job market. 

Hence, the solution becomes AI-driven automated profile analysis applications. Starting from posting an opening, identifying the most relevant job descriptions, shortlisting prospective candidate profiles based on keywords, comparing each candidate’s interview performance, and even their onboarding process can be carried out through an automated process.  The organization gets the best-fit talents for themself, but employees also experience a bias-free recruitment process.   

  1. AI in Employee Training and Development

Timely skill upgradation of employees is the key to a successful business. As the skill criteria of a particular task keep altering with time, it’s essential to provide appropriate learning and development opportunities to employees. But does a generic learning pattern work for all? 

No, the skill upgradation needs of every employee is different, depending on their personal ability, working designation, job responsibilities, etc. Artificial intelligence can quickly identify the individual learning path for employees. So, the HR department can now make each employee uniquely competent for their organizational needs. 

  1. Management of employee profiles

A few years back, employee profile management was a data entry job. Updating employees personal details like address, the number of leaves, approval status of leaves used to be an additional headache for the HR department. 

The employers and employees also had to repeatedly ask for leave approval status, change in address, location updates for inter-company transfers, etc. 

With the help of data science and artificial intelligence, these tasks now need the least amount of human interference. 

  1. Automating the least valuable and mandatory tasks

Answering the common queries of employees and job applicants seems to be very time-consuming and concentration-diverting from primary responsibilities for HR professionals. To fuel up the HR process’s speed and enhance the employees and job applicant’s experience, companies now use automated chatbots. 

So, you are no more liable to keep answering the same questions of employees throughout the day. Instead, you can spend that amount of time analyzing the performance of employees for upcoming appraisal. 

Where does your scope lie in HRM as a data scientist?

The current barriers that HRM faces in implementing AI and ML technology within different HR operations is your ultimate scope.

Although it sounds a bit crazy, these are the hidden opportunities for data scientists now. Within the next three years, these opportunities will lead the HRM. 

  1. Security issues with employees and employee data

While everything is going online, indeed, the data are now more easily accessible by others. The same happens with the employee data. As companies are now using cloud computing services, such ineffective security measures can easily cause employee data leakage. 

This is one of the significant reasons why SMEs still prefer manual HR functions. A data scientist has to provide such an efficient automated ML algorithm that can prevent data leakage too. 

  1. Problem with Appropriate AI implementation

Unlike other technical products and services, AI tools and applications also need regular upgradation for its performance maintenance. With the increasing needs of HR functions and strategies, the ML algorithms have to be altered too. 

Moreover, without following the trends, companies need to focus more on building personalized AI applications to ensure a maximum level of efficacy and security, for these HR departments will need dedicated data scientist/ engineers.  

  1. Incompatible data analysis

Identification of the right data source and collection of valuable data, followed by adequate data clearance, is the first step to efficient data analysis outcomes. Although software tools are now available to perform these HR functions, due to the growing popularity of big data technology, such applications may become ineffective. Here are the great opportunities for data analysts in the HR domain. 

How can you start your data science career transition in the HR Domain?

You can join our Data Science and AI program for experiences program. We offer AI programs specially designed for working professionals. Besides, we provide domain-specific live-project opportunities that will help you grab your very first data science job with greater project experience credibility. 

You can apply for your profile review and telephonic counselling for the courses here.

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