5 Reasons to Use AI in HR
5 Reasons to Use AI in HR
Let's look at five reasons to use artificial intelligence in HR.
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Artificial Intelligence (AI) in recruitment is changing the human resources (HR) game drastically. Today, AI in HR is reshaping the way companies tackle and manage their workforce and make plans, which not only increases productivity but employee engagement in general.
According to Randstad Sourceright research, 76% of 400 global human capital leaders who participated in a research survey accepted that technology is playing a critical role in talent engagement. Around 48% are already investing in creating dashboards for analytics.
“AI will augment HR and give HR time to work on more strategic business issues. The opportunity is to use AI to streamline HR manual processes and provide a more consumer-grade service to employees,” said Jeanne Meister, co-author, The Future Workplace Experience, The People Space.
The not-so-far future of AI in recruitment processes will largely incorporate AI and data analytics to find the best candidates.
Why AI in HR?
The big question is, to AI in HR or not to AI in HR? Bearing in mind that HR has a crucial role to play in boosting company revenue, embracing AI in HR can strengthen your team and help you achieve long-term benefits. With AI, you can take your HR experience to the next level. It can help an organization to handle all processes, such as recruiting, productivity, and retention, more efficiently than traditional HR methods. At the same time, AI allows you to do them faster than ever before. The advantages are many!
Top 5 reasons to use AI in HR
1. Low talent acquisition timelines
Imagine you have 10 positions to fill and have received 2,000 applications for it. How long will it take to go through each manually and then find the best fit for your organization? Quite some time! And not to forget, you are at a constant risk of losing the right candidate because of the long, tedious processes.
By using AI, a plethora of online data can be collected, such as previous job records, social media profiles, educational qualification, and others, distinguishing the rank of each candidate clearly for recruiters to choose from.
This is a huge benefit of using AI in recruitment methodologies, as they allow the recruiter to spend more time evaluating and analyzing only the best-fit. This new technology is designed to automate or streamline certain parts of the recruiting workflow, especially repetitive, high-volume tasks.
For example, software that applies Machine Learning to resumes to auto-screen candidates. In such circumstances, HR units are significantly increasing the quality of hiring decisions. Additionally, organizations save a lot of money this way, as they don’t have to pay the cost of poor hiring decisions.
2. Hassle-free onboarding
It takes a lot for an organization to get the right talent on board. However, hiring is just the first step. Every new employee demands attention, and it is often difficult to commit enough time to each of them.
Productivity is compromised if employees are spending too much time looking for answers to frequently-asked or basic questions. Even if a new employee can identify the one employee or a handful of employees who probably have the information they’re looking for, those people may not always be available, and their time is probably valuable, as well.
This is where AI in HR steps in. With the advent of chatbots, employees can easily ask these questions whenever they come up, freeing HR to handle more complex matters. Also, AI can determine customized onboarding procedures for every single position. It can prove to be an extremely productive practice for a well-planned onboarding program to achieve higher retention rates of employees.
3. Reduced biases
Hiring the best fit for a role is one of the most important aspects of any business, and it isn’t very easy. In most cases, even while CEOs and HR managers implement and adopt programs that they believe to be bias-free, they still fall short of addressing unconscious biases.
“Discrimination is veiled, not explicit, but rather more implicit, unconscious, because we ourselves are unaware of it," Dr. Mzhzarin Banaji, Harvard University professor of social ethics and co-author of Blindspot explains. Therefore, it is expected of leaders to implement ways to reduce and eliminate interviewing and recruiting biases and build a high-performing organization.
If programmed well, AI can help overcome biases to make objective, data-driven decisions. Let’s take an example from Silicon Valley. Eyal Grayevsky, CEO and co-founder of Mya Systems, a San Francisco-based AI organization, aims to reduce bias in recruitment processes by decreasing the influence of humans.
He’s on a mission to give Silicon Valley a more diversified workforce. Along with his team, he is deploying Mya, an intelligent chatbot that interviews and evaluates candidates much like any recruiter. He says that Mya is programmed to judge candidates only on performance-based merit, avoiding subconscious judgments that a human mind can make.
4. Enhanced training of employees
Employee learning and development programs have come a long way. Gone are the days when all assembled in the boardroom to listen to a trainer flip through a PowerPoint presentation, while the rest scribbled notes. With the advent of so many technological changes, it is imperative for all employees to keep learning and improve their professional skills.
AI can successfully plan and organize training programs for all employees, such as online courses and digital classrooms. AI also schedules lessons and determines the best timeframe for new courses to fit the preferences of all employees individually.
5. Efficient performance analysis
It is of utmost importance for HR professionals to monitor the behavior of employees and analyze their key performance indicators. Using AI tools, HR managers can analyze how employees are performing and generate candidate reports.
AI gathers data based on employees' experiences, and projects out the skills and qualities they might have in store to offer the company in the future. Also, AI gathers information from databases to find if employees have enhanced their skills. Managers can then look at the performance rating to decide what promotion, pay, and bonuses the employees might be up for.
AI in HR is here to stay
HR, an industry comprising professionals often known to be overburdened with the complicated processes of managing the lifecycle of every employee, is currently experiencing a major trend in 2019 — The new revolution is Artificial Intelligence.
Companies are planning to leverage AI in recruitment now and in the coming years to help identify data opportunities, increase productivity, and improve internal workflows to name a few.
For instance, using chatbots has truly enabled professionals to utilize their time on more strategic and pressing issues at work while spending less time on operational issues. A chatbot can help in the screening process by getting information about prospective employees and conducting quick background checks.
It makes onboarding truly a self-serve process, as it can talk to employees onsite and interact with workforce management software programs, such as Kronos, Peoplesoft, and Workday. In addition, they can serve as a mobile HR assistant that helps employees get answers to FAQs. The potential benefits are many!
Employees today are becoming increasingly tech-savvy. They are demanding and often willing to leave employers if their needs are not being met. HR organizations can create a better workplace, potentially attracting and retaining talent, by adopting the chatbot technology early on.
How to use AI for diversity initiatives?
Mr. Bot, if programmed right, can work wonders. The importance of diversity and inclusion can be understood by Forbes’ research that used the Cloverpop decision-making database.
The findings showed:
• Inclusive teams can take much better business decisions almost 87% of the time.
• Teams with an inclusive process take decisions 2X faster with 50% of the meetings.
• Diverse teams yield 60% better results.
“This research highlights the potential value of team diversity as a practical tool for architecting decision-making processes,” said Francesca Gino, a professor at the Harvard Business School. She further added, “That our decisions get sidetracked by biases is now well established. While it is hard to change how our brains are wired, it’s possible to change the context of decisions by architecting the composition of decision-making teams for more diverse perspectives.”
Mr. Bot when programmed by unbiased experts, like Pymetrics and Mya systems, can do wonders for diversity and inclusion initiatives, but can be vulnerable to the risk of falling into the hands of biased programmers. Likewise, assessment software provides great AI-based solutions for startups and organizations. These solutions are duly customized for organizational requirements.
Assessment software like HackerEarth works stepwise. The first step typically consists of a coding test for screening, which creates tasks on the basis of the job role and the candidate can access it with just one click.
The second step involves giving recruiters a candidate’s real-time report, facilitating easy shortlisting and filtering. A product like this ensures that you find the best talent purely on the basis of merit and there’s no bias involved. These solutions are fair and help you attract the best talent in the industry.
Be vigilant while handling AI in HR
AI is often praised for eliminating biases. Yet, experts warn that even AI systems aren’t immune to prejudice. There’s a huge amount of risk involved in programming these systems. As AI depends on parameters that reflect the conscious and unconscious biases of humans who program it, it produces cognitive bias.
While AI technologies go through innumerable rounds of tests for biased results prior to implementation, the beauty of this technology is that it learns and grows based on new data received as time goes on.
As new data is not tested for bias, it can yield biased results. If programmed to evaluate biased metrics, then performance reviews based on that criteria will lead to biased results, which aggravates issues already inherent in performance reviews.
The problem scales up when these systems are deployed for mass recruiting. The entire candidate pool can get affected by it. For example, if the systems in a company like Nike that hires 80,000 people a year run with programming that is biased, then the entire recruitment process gets skewed.
How can you program Mr. Bot to avoid goof-ups?
Ensuring that Mr. Bot makes unbiased decisions is entirely dependent on the right kind of programming. Still, to make the initial steps easier, you can add gamification as KPMG did. The global accounting firm deployed a “robot recruiter;” a completely automated system meant for the initial screening of applicants.
Candidates were asked to take a few randomly structured tests. These tests ranged from simple computer shooter-style games with balloons that pop up with mathematics questions on the screen. The process was aimed to test cognitive ability, speed, reaction time, and decision-making.
The organization went a step further and even designed a unique application process for hearing and speech-impaired candidates to ensure that the system remains fair and just. At the same time, KPMG, with its video-based assessment, trained its staff to remove unconscious bias.
Summing up, we would say that Mr. Bot can be our best buddy if we treat him well and nurture him the right way. Welcome Mr. Bot and let him help you shift focus to where it is needed more.
As Larry Page says, “Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.”
We have certainly made great strides in the field of AI, but there is still much to be done. Why not start with AI in HR?
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