Top Hiring Mistakes To Avoid

The HR industry is now leveraging the power of new age technologies such as AI and ML for more accelerated and intelligent solutions. ML helps organisations to significantly improve their process efficiencies at reduced time and cost, without having to compromise on the quality of the outcome.

- Prasad Rajappan

One of the most critical challenges for any organisation is identifying and hiring the right candidate. Organisations are on the lookout for candidates whose profile is aligned with their culture and job fitment. This is because a bad hire is expensive, time-consuming, and, at the same time, works to bring about a drop in the productivity. As per an employer branding agency in London, recruiting, hiring and onboarding costs for a new employee can be as high as $240,000. Today, artificial intelligence and machine learning technologies are at their peak. Investment in AI has accelerated from $282 million in 2011 to $2.4 billion in 2015, an increase of 746% in five years. In 2016, the increase has continued with roughly another $1.5 billion being invested in more than 200 AI-focused companies in 2016.1

We are witness to a rapidly growing interest by the CXOs' in these technologies, and their application across a wide range of functions in various industries to increase organisational efficiency. Artificial intelligence is being applied to all possible aspects of life, and Google is one of the best examples of AI application, since it manages to set your search preferences based on your search history. Popular e-commerce websites use AI as a competitive weapon to automatically suggest users to products in which they may have some interest, on the basis of their recent purchase. Almost every field has a certain use for machine learning and artificial intelligence for their process improvement and enhanced user experience. The HR industry is now leveraging the power of new age technologies such as AI and ML for more accelerated and intelligent solutions. ML helps organisations to significantly improve their process efficiencies at reduced time and cost, without having to compromise on the quality of the outcome.