How AI Helps in the Resolving of Common HR Workforce Issues
Over the last decade, workplace trends have gradually shifted toward remote work and the adaptation of supporting technologies. However, with the arrival of the COVID-19 pandemic, that gradual shift became a landslide change – in just a few weeks. Many HR leaders felt compelled to adapt and scale their operations in order to succeed in a new and foreign landscape.
The best companies know that meeting these challenges begins with a realistic and truthful assessment of their current operations and processes, followed by a firm commitment to the innovation and transformation required not only to cope but also to thrive in this “new normal.”
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Businesses have been increasing their reliance on advanced digital technologies for the past 20 years, and by 2019, more than 85% of major U.S. companies were using artificial intelligence (AI) solutions for HR operations. The rise in new technology adoption is due to the fact that the technologies are not only effective but also analytical in nature and can deliver strong ROI data, such as recommendations for ongoing enhancement and optimization.
Machine Learning, Digital Assistants and Artificial Intelligence: What is the difference
Technology has always played a role in achieving business goals by increasing efficiency and optimizing processes. Artificial intelligence is about to revolutionize how people interact with technology.
Before we get started, let’s describe some of the terms that will be used. While machine learning and artificial intelligence are related and frequently used interchangeably, they are not the same.
Machine Learning (ML)
It is a branch of artificial intelligence that focuses on how computer programs interpret data and learn. Rather than requiring a person to code a program to complete a task, ML can recognize patterns and make predictions that can be used to inform AI. A machine learning system, for example, can catalog employee behaviors to determine whether they are leaving for a new opportunity.
In a nutshell, AI encompasses all of the ways in which computer programs can make intelligent decisions, whereas ML focuses on how AI collects and uses data that has not been explicitly programmed by a person.
Digital Assistants
These are conversational interfaces in which users can ask questions in their own words. Digital assistants, for example, can help new hires complete onboarding tasks and provide assistance on what to do next, and they can ensure employees quickly find the answers they need without having to scour multiple documents or web pages and waste valuable work time.
ML algorithms are used in the development of digital assistants to understand natural language and the intent of a user’s question and to provide intelligent guidance to complete required steps.
Artificial Intelligence (AI)
The computation of human intelligence processes by machines, particularly computer systems, is known as artificial intelligence. AI applications include expert systems, NPL, speech recognition, and machine vision.
How AI Helps in the Resolving of Common HR Workforce Issues
As a capital investment, AI for HR solutions is an appealing option. And, as more businesses turn to AI-powered technologies, many HR executives are searching for a snapshot of the AI HR solutions that are available, as well as how they can meet their specific needs.
AI in HR can help improve every aspect of today’s workforce, from recruiting and training to expanding employee engagement and retention. Here are some of the most pressing HR issues, as well as how AI-powered solutions are addressing them.
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Talent acquisition
A modern business cannot function without effective recruiting. When done correctly, it enables businesses to expand and add value to their respective areas. However, current talent acquisition efforts frequently suffer from a number of issues:
Time-consuming: The average time to fill all roles, according to the Society for Human Resource Management Talent Acquisition Benchmarking Report, is 26 days. Waiting for authorizations, preliminary screenings, and lengthy decision-making processes all slow down the process. Despite new recruiting technologies, the time to hire has increased in most white-collar roles over the last decade.
Reactive rather than proactive: Hiring is frequently required due to turnover or changing needs. While companies should be proactive and constructive, new talent acquisition is often a reaction to past events rather than strategic planning for the future.
A bad hire can cost a lot of money. As per the U.S. Department of Labor, the cost of a bad hire is at least 30% of the employee’s first-year earnings. In addition to the financial costs, bad hires have a substantial impact on employee morale and the productivity of other employees and teams.
Role of AI
SOURCING
Due to one of the tightest labor markets in history, today’s organizations must constantly market their open positions. Using artificial intelligence to improve sourcing can significantly improve an organization’s ability to find the right talent at the right time. It can assist with:
Find the most qualified candidates: Find candidates who have the best fit between the job requirements and their skills and experience. ML algorithms learn synonymous words that are frequently used in resumes, going beyond a simple search for key terms.
Make job recommendations to candidates: Prospective candidates who are discovered through organic search activity or a targeted campaign are encouraged to apply for open positions. AI can notify the right candidates with the appropriate skill sets about available jobs before they are posted.
Predict the performance of the candidates: AI-based candidate matching calculates a candidate’s possibility to accept a job offer, projects performance outcomes, and estimates their expected tenure using HR data.
SCREENING AND INTERVIEWING
The use of digital assistants for a more engaging candidate experience is a significant benefit of AI at the interview stage, which can:
Assist candidates in becoming more self-sufficient: They have complete control over the interviewing process, from rescheduling or canceling to sending reminders, sharing notes, and recommending resources for review.
Assist HRs: AI reminds them of impending interviews and provides candidate information. AI can also assist in overcoming subjectivity by collecting data from previous employees in similar positions and developing targeted questions for hiring managers. This focuses on the candidate’s skill set, provides more context on the nature of the job, and compares to similar roles in other organizations.
SELECTING AND OFFERING
While ML applications should never be used to make final hiring decisions, AI can assist recruiters and managers in making better hiring decisions. It enables them to:
Analyze candidates against current top performers: Utilize benchmark data and artificial intelligence to compare job candidates to others who have excelled in similar roles within the organization.
Create personalized offers: Analyze the wealth of data points in relation to the local market and listed salaries by rival companies, providing a nuanced and strategic view of how roles should be banded. Taking it a step further, AI can improve recruiting efficiency by matching a specific offer with individual job and employee backgrounds to calculate the likelihood of acceptance.
Predict candidate behavior: Predict a candidate’s possibility of accepting, performing, and remaining in the role being offered.
ONBOARDING
Onboarding is important because it establishes the tone for the employee’s tenure. According to Work Institute research based on 34,000 exit interviews, approximately 40% of new employees quit within the first year of employment. According to the Work Institute, three-quarters of that turnover could have been avoided if onboarding had been managed more efficiently. AI aids in:
Reduce administrative burdens: Deliver and receive necessary paperwork, company policies, and login information through automation. AI can monitor which documents have been read, capture electronic signatures once steps have been completed, and eliminate the need for HR to manually follow up.
Allow 24-hour onboarding: Digital assistants streamline the process by guiding new hires through all necessary onboarding steps and preemptively suggesting the next steps to help them ramp up quickly in their roles.
Reduce time to productivity: AI-powered digital assistants can recommend job-related learning based on successful employees in similar positions, and they can also provide relevant content such as books and journal articles.
Talent management
Companies that want to engage their employees face ongoing challenges with employee retention. One area that is still receiving attention is talent management, which is being driven by a workplace where multiple generations work side by side and are becoming increasingly purpose-driven. Nonetheless, many companies have yet to fully accept the opportunity of modern talent management, resulting in high turnover due to the:
Passive career advancement: Companies struggle to meet workforce expectations for career advancement.
Typical succession planning: Many businesses remain reliant on reactive succession planning, leaving them unprepared when employees leave.
Undifferentiated, rigid learning: Traditional learning offerings fall short of meeting evolving demands for more diverse learning styles and learning content that anticipates future skill requirements.
Expectations for compensation: While employers use market data to establish compensation expectations, workers continue to look for better opportunities even after accepting an offer.
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Role of AI
By creating an environment that meets employee needs and improves retention, AI can help organizations realize the full potential of talent management. Such technology has the potential to personalize career development, optimize succession planning, close skills gaps, and steer compensation strategy, assisting managers, leaders, and managers in developing and deploying talent, resulting in strategic advantages for the business.
CAREER DEVELOPMENT
The evolution of how job seekers and employees achieve career advancement is one of the emerging nuances of work. Workers used to stay with their employers for the duration of their careers, rising from entry-level positions to positions of leadership. Employees can now move at a much faster rate thanks to a faster-moving economy, more frequent layoffs, and emerging startups. According to some data, millennial AI can provide an employee with intelligent suggestions for courses or reading that will help with day-to-day job duties. Organizations must take a strategic approach to career development in order to retain employees. Employees expect to be given learning and career opportunities that will help them advance in their careers and achieve their goals. AI provides:
Personalized recommendations: Employees can receive curated career development recommendations that change with the business and help them achieve their maximum career potential. Carefully crafted content not only supplements manager guidance but also demonstrates to employees that their companies are invested in their careers.
Individualized career development: AI gathers and delivers insights about each employee’s career progression in a personalized manner. Each individual can chart their own career path, which is linked to the specific learning experiences needed to bridge current and projected skill gaps. One of the most effective ways to encourage learning is to provide employees with the clarity and tools they need to make career changes.
COMPENSATION
The employment market’s ongoing concern is compensation, as workers seek to be compensated for their worth. Employees in this tight job market are confident in seeking new work opportunities or requesting pay raises in order to improve their quality of life. In this environment, employers must also ensure that the appropriate compensation is paid for the appropriate positions in order to avoid paying too little or too much. Leaders must think strategically and investigate competitor trends in order to meet employee expectations and retain top talent.
With HR evolving, it is critical to change how compensation is determined. Organizations require more data to develop a strategy that works for their people and accounts for differences in expectations, roles, and skill sets. AI aids in:
Provide market insights: By analyzing a wealth of salary data points relative to the local market and available competitor data, AI provides a nuanced and strategic view into how roles should be banded.
Increase recruiting efficacy: By aligning a specific offer with individual job and employee backgrounds to calculate the likelihood of acceptance.
Tips for Using Artificial Intelligence in the Workplace
Empower managers: Managers should be given more authority. The ability to learn and adapt is one of the most powerful features of AI and machine learning. The best companies allow management and team leaders to provide input and question AI outcomes, then iterate until it is perfect for their specific team’s needs.
Keep a lookout for bias: AI is bias-free by definition, but human biases can be accidentally programmed or validated through spurious correlations. From the start, reliable data and AI governance policies and best practices are required. The good news is that there is a lot of support in this area.
Provide transparency: HR executives must explain or defend the requirements used for job descriptions, hiring recommendations, advancement, and layoffs, among other things. Transparency from the beginning protects both the company and its employees.
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