Almost 23% of companies using AI have said that they are doing so in the recruiting and human resource domain, according to a 2018 Gartner Inc. study of more than 800 respondents. As companies across all sectors compete against each other to hire the best talent, the latest technology is playing a crucial part in giving you an edge over the competition.
A research conducted by LinkedIn shows that 46% of recruiters have mentioned ‘finding the right candidate’ as the biggest challenge today. The process of recruiting has always been rather burdensome for the HR for mainly 2 reasons: the repetitive manual tasks that slow down the process and the lack of data for making the right decisions.
But big data, predictive analysis and artificial intelligence are transforming the entire HR tech ecosystem and providing robust solutions for problems which were hitherto plaguing the industry. Technology is helping overcome biases with processes that are hyper-responsive to market data, complex metrics, and even budget constraints.
Here are 5 tech buzzwords related to AI recruiting that we here a lot:
Big Data: The process of collating, analyzing and correlating vast amounts of data from different sources to make predictions and gain insights can broadly be defined as big data. However, it is so much more complex than that! While big data is not AI, AI without big data would not exist. These insights in turn result in better decision making for humans and machines, thereby minimizing human errors, mitigating biases and saving costs.
Automation: Automation mimics human behaviour. The main benefit of automation is that it takes care of the manual repetitive tasks that most recruiters dread doing, freeing up time for more meaningful tasks and human interactions. But automation can also come with some cons. The main one being that sometimes suitable applicants are rejected because of a mismatch of words. Also, since predefined rules control automation, human intervention is needed to modify the code to bring about improvements.
Predictive Analysis: Think of predictive analysis like an ‘educated guess’ that we humans make. Predictive analysis is something like that, but infinitely more accurate and dependable. Predictive analysis studies the patterns in big data to draw conclusions and make predictions. Based on these patterns, predictive models are built to enhance the decision-making process. Predictive analysis transforms hard-coded rules into “adaptive logic” that produce better results.
Machine Learning: Machine Learning is a subset of AI that trains machines to learn (without help from humans), based on the automatic application of complex mathematical calculations to Big Data over and over again to identify patterns. The machines learn with each iteration’s findings and as fresh data is introduced over time. Based on this, predictive models are built.
AI: Computers are helping humans with complex decision-making, problem solving and learning. Artificial Intelligence is helping in optimizing processes, automating manual tasks and influencing outcomes based on things that humans are unaware of, using data to make accurate decisions. Self-learning algorithms are saving the day when the scope of data and the scale of the problem are just too big for human interaction.
Fact check- AI recruiting does not eliminate the need for human intervention. It just supports and optimizes the recruiting processes. Human instincts, knowledge and decision-making are what help an organization find the best possible team. Technology merely augments the process, making decisions that are data-centric; preventing bad hires and saving costs in the process.
