Artificial Intelligence has come a very long way from being just a concept to reality. There are a few reasons why the power of AI assistants will be so game-changing for HR. The first is that certain HR tasks are the types of time-consuming, administrative tasks that keep teams from achieving the higher level work that drives towards larger goals.
Tasks an AI assistant could conveniently drop into a direct or group message are:
Reporting on surveys and company analytics. A bot could send you a report of how many managers are awaiting approval for next hires, or how many candidates you’ve interviewed and hired over the last quarter.
Scheduling, particularly group meetings or interviews which require coordinating multiple calendars.
Improving workflows by saving employees from distraction: such as gathering and sending someone a briefing sheet before an important meeting.
AI has steadily gained importance across all verticals of organizations like Marketing, IT, Sales to name a few. Since HR is a strategic business function, there is a vast scope in this vertical to adapt to newer technologies, for example, software applications like Human Capital Management have successfully embedded AI functionalities into its core processing engine and have proved to be a game changer.
HR strategies for the future are focusing on creating an agile, employee-focused and digitally enhanced the dynamic environment and AI will have a tremendous impact in implanting this vision as it covers the four pillars of HR namely- the AERD (Attract, Engage, Retain and Develop).
Here’s how AI makes enormous impact on HR:
You can’t fool a bot!
Yes, you heard it right.AI are way ahead intelligent systems. Amazon’s Alexa is being used by nearly 1.8 million people in the world. A robot might have a more in-depth interview with a job applicant, while showing no bias toward the candidate, CEO of artificial intelligence engine developer Recognant Brandon Wirtz reasoned. “Sometimes it comes down to ‘This candidate reminds me of someone I didn’t like in high school,’ or ‘This person and I have bonded over the same hobby,'” he suggested. “Computers don’t have these biases.”
Scheduling, scheduling, and rescheduling. The bane of many of our existences, yes? Well, AI is poised to be a game-changer when it comes to workflow problems. According to a recent com article, the next few years should see software that automates hiring processes like “interview scheduling, employee performance reviews, employee onboarding, and even the answering of basic HR questions.” I, for one, can’t wait.
Grabbing big data by the tail
With the increase in natural language processing, previously unforeseen amounts of data and the technology available to handle it all, the groundwork has been laid for a potentially massive migration to AI applications in business. With this migration comes the promise of smarter and timelier insight, better efficiency and time saved, and algorithms that constantly improve for as long as the data keeps churning. Machine learning, natural language processing and cognitive computing are among the new artificial intelligence terms HR managers are confronting in vendor literature.
Better prediction models
AI will get to know your company almost better than you do. Whether it’s predicting future turnover rates, reduced (or increased) employee engagement levels, concerns about internal employee communications, project completion problems, and any other unexpected hidden issues that would usually take years to surface, artificial intelligence will (most likely) be one step ahead of you. And when it comes to cost savings and overall organizational efficiencies, that’s a very good thing.
An AI-powered Chatbot can respond to the most common HR queries and it can schedule the meetings with you and your HR. Through HR analytics it can empower immediate managers to make better decisions through various information — Learning pattern, Performances Track records.
AI enables personalized learning programmes based on employee information skill set, experience, behaviors and learning patterns, recognition pattern.