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Machine Learning Can Teach Your Workforce Featured

Machine Learning Can Teach Your Workforce "Programming "

Artificial intelligence and machine learning are making their way into the business in a big way. Every time you speak to the executives of big or small companies, you will not end the conversation without hearing their plans for investment in machine learning (ML) or artificial intelligence (AI). One of the areas that have benefited immensely from ML/AI is human resource management. Although this sector has experienced significant changes in the past few years due to the evolution of technologies, arguably, none of them has transformed HR like AI and ML. Here are some ways that artificial intelligence and machine learning are helping in human resources:

  1. Reduces bias in appraisals

The biggest challenge of any human resource manager during performance appraisals is to appraise employees without bias. This is often difficult because humans are naturally biased. With the help of AI/ML algorithms, analysis can be done beyond the usual spreadsheets through the execution of employee assessments via continuous appraisals. The AI/ML algorithms can be used to estimate the employees’ career paths and prepare them for the advancement of their careers. 

  • Estimating employee morale

The human resource industry is leveraging AI and ML in the identification of employee patterns over time. Technologies such as facial recognition are capable of measuring employee emotions on a particular scale and even differentiating gender. The reports and data gathered can be used to develop solutions by deriving insights and acting on them. The insights can lead to the development of strategies to boost employee morale and enhance their potential in places of work. 

  • Skill management

Machine learning is showing high potential in enhancing the management and development of individual skills. While this area is still in its initial stages, AI-based platforms can be calibrated to guide the development and management of individual employees without the intervention of human coaches. This not only saves time but also provides the opportunity for more people to be managed to grow their careers and remain engaged all the time. An example of the use of ML in skill management is Workday, a company that builds personalized training recommendations for employees based on the needs of the organization and the specifics of an employee. With machine-based feedback, individuals can learn a lot and grow into their jobs. 

  • Streamline hiring processes

The hiring process is often difficult and employers end up getting candidates who are not up to their set standards. However, with AI/ML, every stage of the hiring process is enhanced by availing data given by personalized research tools. These tools and data allow organizations to find the best talent in the industry with the specific traits that meet employer’s desires. An applicant tracking software can help HR recruiters by analyzing numerous resumes and reducing the ambiguities encountered during recruitment. The AI-based software can analyze several resumes based on specified keywords, location, skills, and the applicant experience. 

  • Payroll processing

Payroll processing is one of the complex tasks that HR managers have to face regularly in their operations. With the help of ML and AI, payroll processing and employee expenses management can be taken care of with the help of HR bots. With these bots, you may not need to spend too much time filling many forms that are necessary for the documentation of business expenses. Rather, you can just notify the bot, which will process everything and get your bills approved by your manager. This simplifies work for the HR personnel and enhances accuracy. 

Artificial intelligence and machine learning technologies are proving crucial for operating businesses. For the human resource aspect of the organization, it allows organizations and HR teams, in particular, to easily manage various day-to-day processes, overcome hurdles and assure operational efficiency.

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Scott Koegler

Scott Koegler is Executive Editor for PMG360. He is a technology writer and editor with 20+ years experience delivering high value content to readers and publishers. 

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