HR has evolved significantly in the last few years, thanks to AI. Artificial intelligence and Machine Learning is redesigning the way companies hire and manage their workforce.
Recruitment is no more a monotonous process for HR practitioners as all the time-consuming and repetitive tasks are now managed by smart technologies giving HR experts ample time to focus on more meaningful activities.
We let the thought leaders visualize the future while we take a dive into what’s helping HR and taking it to the next level in the present. The biggest advantage of ML is that it reacts faster than humans in identifying insights and inferences that might otherwise take plenty of manpower and time or not be identified at all. In the following examples, we see how machine learning can aid everyday decisions related to organizations and their workforces:
Making recruitment effortless
From evaluating millions of profiles in seconds, to candidate screening and assessment, machine learning is making the tedious, age-old recruitment process super fast and efficient. Algorithms are enabling HR to detect patterns faster and more accurately than human beings and programs can correlate candidates’ past experiences and relevant skills to determine where they may find the fit best in the company.
HR practitioners are discovering that this kind of advanced analysis and pattern recognition can greatly increase the success rates of hiring decisions. Further, with more innovation, the possibilities seem endless, especially in combinations of individual factors and patterns.
Confusing candidate engagement
Studies suggest that fifty percent of candidates don’t receive any type of communication or have any type of interaction with an employer once they apply for a role or come on board. With the help of algorithms, candidate engagement can be automated and made unique not just during employee onboarding but post that also. The interactive algorithms can help the new employee with relevant information regarding team, domain expertise and more.
While the area of employee engagement will always have a large human, tactile component – ML can help identify trends by understanding what it is that keeps employees happy at their organization. This can be done by having data from a common platform ingested into an ML system, which understands and provides numerous ways in having engagement campaigns driven. Ultimately, this helps in preventing attrition, building a motivated and committed workforce and ultimately impacting productivity.
Reducing bias in appraisals and career progression
Algorithms could also be trained to perform appraisals through regular, unbiased performance reviews. One of the many challenges for supervisors during performance reviews is for them to remain impartial. AI algorithms could evaluate performance data without any personal bias for the candidate.
Similarly, organizations can also use AI to map employees’ career paths and gear them up for career progression. Employees may need support with customized training and learning information that supervisor may not always provide. With AI, organizations can democratize learning and development initiatives for each employee at appropriate timelines. AI can also examine past performance trends of individuals, teams, or departments and predict future outcomes. This information can give HR directors insight into the steps to take to improve performance or morale when the AI software spots a potential problem.
Gauging workplace morale
Machine learning is extremely good at detecting patterns over time, even with a limited number of variables. Hence, many organizations are using it to understand employee behavior at the workplace, which in turn helps them assess employee productivity, workload, moods etc. All these factors can help them determine the overall workplace morale and take relevant action in areas of concern. This would almost be impossible to gauge from a simple spreadsheet analysis.
HR functions are very important to propel business growth. We need to embrace digital HR by equipping itself with AI and ML-powered technologies for solutions. With millennials taking up to 70% of the jobs by 2020, HR needs to develop its technology progressions to meet organizational needs and employee expectations. Are you tech-ready for the future of work?
If you like our article and would like to share your views, please drop your comments below.
From India, Noida
2Recruitment is no more a monotonous process for HR practitioners as all the time-consuming and repetitive tasks are now managed by smart technologies giving HR experts ample time to focus on more meaningful activities.
We let the thought leaders visualize the future while we take a dive into what’s helping HR and taking it to the next level in the present. The biggest advantage of ML is that it reacts faster than humans in identifying insights and inferences that might otherwise take plenty of manpower and time or not be identified at all. In the following examples, we see how machine learning can aid everyday decisions related to organizations and their workforces:
Making recruitment effortless
From evaluating millions of profiles in seconds, to candidate screening and assessment, machine learning is making the tedious, age-old recruitment process super fast and efficient. Algorithms are enabling HR to detect patterns faster and more accurately than human beings and programs can correlate candidates’ past experiences and relevant skills to determine where they may find the fit best in the company.
HR practitioners are discovering that this kind of advanced analysis and pattern recognition can greatly increase the success rates of hiring decisions. Further, with more innovation, the possibilities seem endless, especially in combinations of individual factors and patterns.
Confusing candidate engagement
Studies suggest that fifty percent of candidates don’t receive any type of communication or have any type of interaction with an employer once they apply for a role or come on board. With the help of algorithms, candidate engagement can be automated and made unique not just during employee onboarding but post that also. The interactive algorithms can help the new employee with relevant information regarding team, domain expertise and more.
While the area of employee engagement will always have a large human, tactile component – ML can help identify trends by understanding what it is that keeps employees happy at their organization. This can be done by having data from a common platform ingested into an ML system, which understands and provides numerous ways in having engagement campaigns driven. Ultimately, this helps in preventing attrition, building a motivated and committed workforce and ultimately impacting productivity.
Reducing bias in appraisals and career progression
Algorithms could also be trained to perform appraisals through regular, unbiased performance reviews. One of the many challenges for supervisors during performance reviews is for them to remain impartial. AI algorithms could evaluate performance data without any personal bias for the candidate.
Similarly, organizations can also use AI to map employees’ career paths and gear them up for career progression. Employees may need support with customized training and learning information that supervisor may not always provide. With AI, organizations can democratize learning and development initiatives for each employee at appropriate timelines. AI can also examine past performance trends of individuals, teams, or departments and predict future outcomes. This information can give HR directors insight into the steps to take to improve performance or morale when the AI software spots a potential problem.
Gauging workplace morale
Machine learning is extremely good at detecting patterns over time, even with a limited number of variables. Hence, many organizations are using it to understand employee behavior at the workplace, which in turn helps them assess employee productivity, workload, moods etc. All these factors can help them determine the overall workplace morale and take relevant action in areas of concern. This would almost be impossible to gauge from a simple spreadsheet analysis.
HR functions are very important to propel business growth. We need to embrace digital HR by equipping itself with AI and ML-powered technologies for solutions. With millennials taking up to 70% of the jobs by 2020, HR needs to develop its technology progressions to meet organizational needs and employee expectations. Are you tech-ready for the future of work?
If you like our article and would like to share your views, please drop your comments below.
From India, Noida
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