Impact of Machine Learning on HR in 2023
Since the last decade, technology has been an integral part of all businesses. It is now the most critical factor determining the success of all business operations. New-age technologies like artificial intelligence and machine learning help drive greater efficiency and productivity and improve other business metrics. Until 2021, the machine learning market was estimated to be around $15.44 billion and is expected to grow at a CAGR of 38.8% in the next five years.
Machine learning has recently found newer applications in the healthcare, education, and HR technology industries. This development has opened more doors of opportunities for people seeking skilled jobs and organizations seeking to invest in human capital. Irrespective of which career path you may choose, being familiar with these technologies will give you an edge over those who are not.
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The Impact of Machine Learning on HR
The impact of machine learning on the HR industry can be seen in various areas, like predictive analytics, talent acquisition, employee engagement, performance management, and training and development. Machine learning algorithms can analyze vast amounts of HR data to identify potential candidates and predict their chances of being shortlisted for a particular job, enabling HR professionals to make better data-centric decisions.
When it comes to talent acquisition and management, ML algorithms analyze resumes, job descriptions, and applicant data to streamline the hiring process and save a lot of time that goes into shortlisting candidates. On top of this, with developments in natural language processing (NLP) techniques, with tools like Alexa and Siri, HR functions are greatly aided by intelligent bots/chatbots. Consequently, the HR team will have more time and resources to devote to all crucial human contacts and work on more strategic projects.
Machine learning can also assist HR teams in identifying and resolving problems with employee engagement. These algorithms can find trends and patterns causing poor employee engagement by examining data from employee questionnaires, performance reviews, and other sources.
5 Ways in Which Machine Learning can Transform Human Resources Function
Source: Code Tiburon
Machine learning can revolutionize how human resource management works in organizations. Here are some obvious ways machine learning can transform the domain.
1. Job Seekers/Applicant Tracking and Their Assessment
Source: AI Multiple
Early machine learning applications have prioritized candidate tracking and evaluation, particularly for businesses and positions that receive a lot of applications. Many companies use AI and ML tools to better workflow, cut costs and improve the employee experience. They utilize machine learning to shortlist and track the candidates with the most appropriate qualifications and skill sets. By tracking a candidate’s progress during the interview process and facilitating quick feedback to candidates, machine learning systems aid HR and management employees in hiring new team members.
2. Smoother Onboarding
The impact of machine learning on HR departments can also be seen during the onboarding process. Incorporating machine learning and artificial intelligence with the onboarding process can add a personal touch while making it time-savvy and more efficient. Machine learning helps with
- Customized Onboarding Plans: The algorithms can use the employee’s role, talents, and experience to build customized onboarding programs. Candidates may feel more engaged as a result, and they may adjust to their new roles more rapidly, enhancing the candidate experience.
- Facilitating Paperwork: Filling out paperwork, including tax and benefits enrollment forms, can be automated with machine learning, saving time and minimizing errors.
- Feedback: During the onboarding process, employees can provide inputs that machine learning algorithms can analyze to find areas for improvement and make changes for future hiring.
3. Predicting Attrition (Rate of Detention)
Attrition refers to the tendency/rate employees might drop out of an organization. Thankfully, machine learning can help organizations be prepared before an employee leaves the organization by predicting attrition. ML predicts attrition by analyzing large amounts of employee data and identifying patterns and predictors of turnover. The algorithms can collect and analyze employee data, surveys, and HR records to identify contributing factors. After the analysis, the algorithms specify certain features like workload, employee experience, compensation, work-life balance, etc. This way, machine learning can utilize predictive models and real-time monitoring to see which employees will most likely leave the organization.
4. Addressing Common HR Challenges
Source: Code Tiburon
By offering data-driven solutions and automation, machine learning can assist in addressing typical HR difficulties. HR professionals can oversee a lot of tasks that machine learning algorithms can quickly perform. Some of these tasks include:
- Diversity and Inclusion: It can be used to spot biases in hiring decisions and offer solutions for how to deal with them. This can assist businesses in developing more inclusive and varied workplaces and guarantee that every employee has an equal chance to succeed.
- Training and Development: Employee skill gaps can be found using machine learning, which can ultimately suggest training courses to close those gaps. Employees may use this to enhance their work output, develop their careers, and/or enjoy their jobs more.
5. Machine Learning and Artificial Intelligence in Enterprise Human Resource Management
Enterprise management has already witnessed machine learning in nascent forms, but it is yet to scale. Massive companies like KPMG are leveraging large-scale and customized “Intelligent Enterprise Approach” in which almost all verticals leverage predictive analytics and human resource management to help optimize all performance indicators.
Other companies like Google have also been working on building big data and performance management for several domains, including human resources. Its People Analytics department is responsible for solving problems catering to employees and their tenure in a company.
It is because machine learning can improve:
- Limiting factors in the interview process.
- Management of leaves, like maternity/paternity leaves.
- Managing department sizes.
- Creating customized onboarding propaganda for each selected employee.
5 Advantages of Using Machine Learning in HR Processes
The amalgamation of machine learning algorithms and techniques with HR functions leaves room for HR professionals to take on more responsibilities and streamline the hiring and management of employees. Specifically, human resources and machine learning together bring the following benefits
1. Improved Efficacy of the Recruitment Process
Searching and shortlisting worthy candidates after hours of screening resumes is a strenuous task. Machine learning can reduce the time you spend sorting through applicant data and validating typical recruitment operations, such as evaluating resumes, organizing interviews, and responding to inquiries from possible applicants.
Machine learning algorithms:
- Narrow down your applicants by sorting the most relevant skills for the job.
- If programmed carefully, the algorithms can minimize sorting biases that sometimes alter the screening process.
- Perform background checks on applicants and ensure their previous work experience is legitimate.
2. Developing a Better Training Strategy
Using machine learning technologies in your employee training programs allows you to customize the learning experience for each individual. It can be used in sessions to gauge employee knowledge and suggest specific training courses to get them up to speed.
It can also be used to sort through training analytics for the organization to identify which staff require more training. Or even to assist in determining potential job choices based on training history and requirements.
3. Better Employee Retention
Another impact of machine learning on HR is in the employee retention domain. Machine learning and artificial intelligence can together predict employee retention rates by using existing data to analyze trends. These technologies can also analyze employee performance based on job titles and demographics. More analyzing and categorizing criteria can be added to the algorithms during the programming phase, making the filtering process more efficient.
4. Better Workforce Planning
Machine learning can assess historical and current data on employee performance, job functions, and abilities to assist HR in making knowledgeable workforce planning decisions. Consequently, it can better understand how the company has been allocating work and how it has resulted. By doing so, the organization can ensure the right people are in the proper roles and improve its hiring, training, and development strategies.
5. Simplifying Day-to-Day HR Functions
As machine learning technologies are accessible round the clock, they can reduce the need for human resource professionals to monitor the processes constantly. Moreover, these technologies significantly eliminate the errors that humans might commit throughout the day. For instance, you can automate the daily attendance using ML and AI so that employees can directly check themselves in without going to HR. Or you can also automate the task of scheduling interviews.
Looking forward to the future of machine learning and artificial intelligence, the technologies have a much higher potential when scaling data-driven operations and decision-making. Even on the employment side, the machine learning industry is home to more than 2.3M jobs for skilled professionals and offers some of the most lucrative pay scales. More recently, the HR industry has also adopted machine learning and artificial technologies across many applications like
- Talent acquisition,
- Performance management,
- Workforce planning,
- Employee engagement.
Especially since the onset of the COVID-19 pandemic and the months following it, almost all organizations welcomed remote working arrangements. This paradigm shift made technology adoption inevitable. Due to this advancement, the human resource market was valued at $19.38 billion until 2021, with an expected CAGR of 12.8% until 2030. Within just one year of massive-scale machine learning adoption, the market size was valued at $21.48 billion in 2022!
Source: Grand View Research
The future of HR machine learning holds room for newer and more complex applications like
- Revolutionizing the resignation landscape,
- Reskilling and upskilling,
- HR analytics, and automation.
Sounds lucrative? It surely is. If you want to know and learn more about machine learning (in general) and its applicability in human resources, you can refer to Analytics Vidhya. Analytics Vidhya is a leading ed-tech platform that hosts a wide range of resources, like blogs and courses on data science, machine learning, and artificial intelligence. Here are some resources you can refer to at Analytics Vidhya:
- Tutorials: The website features many video tutorials on machine learning, machine learning in HR, and other related sub-topics. These tutorials provide detailed information on how machine learning algorithms can be used for predictive analytics, employee sentiment analysis, etc.
- Blogs: Analytics Vidhya posts numerous blogs, each hosting a series of well-researched articles on machine learning, data sciences, artificial intelligence, and ML in human resource management.
- Community of Contributors: A thriving community of data scientists and machine learning practitioners at Analytics Vidhya can assist with education and problem-solving in the real world. The community provides various tools, including forums, debates, and competitions, which let users communicate with experts and gain knowledge from their experiences.
Frequently Asked Questions
Q1. How does machine learning affect HR?
A. Machine learning significantly affects HR technology. Large datasets can be analyzed by HR departments using machine learning algorithms to find trends and insights about employee engagement, performance, and retention. This can help with hiring, training, and development initiatives and make it possible to predict staff turnover more precisely. Machine learning can automate administrative activities like organizing interviews and screening resumes, freeing up HR personnel to concentrate on more strategic projects.
Q2. How will technology affect HR in the future?
A. HR will continue to change due to technology since it will allow for increased productivity, data-driven decision-making, and better employee experiences. HR departments will have access to even more advanced technologies for data analysis, result prediction, and work automation as artificial intelligence and machine learning continue to advance. This will help HR professionals make better hiring, performance management, and talent development decisions, resulting in better organizational performance.
Q3. What is the future of HRM?
A. HRM is an emerging field, and several trends will continue to grow in the coming years.
- One significant trend is the development and continued use of technology, especially artificial intelligence and machine learning, to enhance HR procedures and decision-making. Predictive analytics may detect future problems and possibilities within the workforce and use chatbots and virtual assistants for employee interactions.
- Another trend is the growing emphasis on the employee experience, with HR departments taking a more active role in fostering a supportive work environment and offering specialized support to specific individuals.
- HR departments have also lately focussed on making the onboarding process much more smooth for employees. This helps in improving the rate of employee retention and company loyalty.