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The workplace landscape has dramatically changed over time. Managing people resources have become more complex. In the past, the primary role of HR was to identify the right candidate, test their caliber and provide offer letters. Areas such as employee attrition and career growth were considered important, but not the primary focus of HR.
As articulated by Jack Welch, in the new business model HR plays the key role along with Finance for the success of the company. The department is now recognized and seen as a driver - assisting the organization's key business objectives. Some industry experts opined that the competition among enterprises depend largely on the functioning of HR professionals - that are indeed the most valuable assets of any corporate body.
What exactly happens when AI is applied in HR? A judicious blending of human and machine-based intelligence takes place, which can widen the scope and range of HR, once considered an exclusive realm of a behavioral discipline, into a highly scientific and tech driven that can systematically impact daily recruiting, assessment, management of in-house personnel movements and many more.
Talent acquisition is one of the key responsibilities of HR departments. The conventional method of recruitment followed for years, include interviews, written examinations, referrals etc. The pertinent point is how we can ensure that the candidate has the "talent" that is eventually required HR departments have to put up with an impression gained in an hour or so at the time of the interview to finally decide whether one is in or out. AI technology promises to streamline this process by relying more on the analytical processing of huge amounts of data instead of on individual observations.
Hiring managers no longer have to manually source, screen applicants. Instead, they can solely rely on machine learning to offer intelligent recommendations which can suggest candidates sourcing them from multiple sources including Job boards, social media, etc.
AI relieves HR departments of the huge burden of sifting through terabytes of data that make up candidate's resumes, social media accounts, reference letters and other sources. Thanks to its robust analytical capacity that allows AI to go through huge amounts of data about numerous candidates at the same time, these laborious and risk ridden processes have become things of the past. AI can also help post-hiring performance assessments, which offer valuable insights into the applicant's potential.
Artificial Intelligence coupled with machine learning can significantly improve employee on boarding process. It can be used to facilitate a regular touch point with a new candidate joining the company.
Learning and Development
Based on historical data, employees can be recommended for the best learning courses with the use of machine learning. The advantage of using tools here is the capacity to personalize learning based on a person's profile, job experience, past learning patterns and skills needed to succeed in the job.
Managing attendance, time and leave
Machine learning tools are assisting companies to understand the trends of leave with respect to the performance of employees. Recording attendance has moved from manual register to biometrics, to mobile apps to even CCTV based interfaces - where facial recognition is used to capture time and attendance.
Machine learning systems measure, analyze and report on employee engagement and general feelings related to their work.
The present challenges of the HR department are mainly retention, behavior tracking, skill up-gradation etc. On the basis of available data of employees like age, education, department, last promotion, job satisfaction etc., machine Learning tools can help predict the reasons behind employee turnover. It will allow the managers and HR department to understand the critical factors of employee turnover better and use the information to enhance the work environment and reduce attrition.
In the world of people management and human resources, data has to be gathered in a wide array of areas - from employee attitudes and feelings to past experience, to compensation management. HR analytics can almost accurately predict factors such as employee performance, attrition, and even adverse events, such as unethical behavior. The major challenge that many HR managers face during performance appraisals is to remain unbiased. Using machine learning, one can help carry out employee assessments through regular, unprejudiced performance evaluations.
Where there will always be critics and skeptics, the current landscape shows that HR will increasingly start leaning towards machine learning. Ultimately, the goal of every HR and talent function is to rise above the fray of tactical day-to-day activity and tend to achieve a potential & impactful 'seat at the table' in developing the core business strategy.
It does not mean AI does not have any limitations in HR. The newer concept like affirmative action, reservation of jobs for particular classes, communities and sub groups etc. are not possible in the AI regime. The machine does not have any emotions and is driven by logic that is fed into.
Indeed, the technology has played a crucial role in transforming Human Resource Management from personnel management to business execution, but the key point to notice here is that the technology itself does not create this change. Rather HR managers leverage technological disruption to drive real value to the business.
Escalating the business will be the top enterprise level objective in 2019 for CHROs (Chief Human Resource Officer). To leverage this opportunity, their main focus will be to build critical skills and competencies for the organization, to strengthen the current and future leadership bench, and to improve the overall employee experience in volatile and uncertain environments offered by technological disruption in 2019 and in the near future.
So, to compete in this digitally transforming world, organizations should embrace technological disruptions to open doors for agile HR Functions.
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