Hiring Solved: How this Eightfold.ai Has Solved the Hiring Process through A.I.

<p>What if there was a software that could take the guesswork out of finding a career or an employee? And what if that software could not only analyze your technical skills, but also those that could lead you to leadership positions down the road? That would be great news for the hiring managers and everyday Americans who struggle with and feel anxious about the complexities of completing a job search. Lucky for them then, that Eightfold.ai is working to make those worries a thing of the past through artificial intelligence.</p><p><i>“What we are doing is using the latest advances in deep learning and machine learning to really understand, not what people have done, but what they are capable of being next. What is their learning ability for a certain skill? If you know statistics and signal processing, you can learn machine learning very quickly. If you are good in programming, you can learn Python quickly. So really trying to understand the learning ability of each individual and using that to assess and understand who can be a great fit in what enterprise, in which function.” </i></p><p>With more than 100 customers, including AT&T, Cisco and Liberty Mutual, Eightfold.ai is using the power of data to solve the complexities that come with hiring thousands of employees. On this episode, Ashutosh Garg, discusses how A.I. can be used to identify which candidates are an ideal fit for an organization, and he gives an inside look at their process and the variables they look at to identify that perfect candidate.</p><p><strong>Main Takeaways</strong></p><ul><li><strong>It’s a Problem Rooted in Data:</strong> When you’re building any application that’s rooted in A.I., the number one priority needs to be data collection. The more data you have, the more inferences you are able to make. When Eightfold.ai launched its platform, it only worked with companies that hired more than 10,000 employees over a few years. The idea is that for every 10,000 employees hired, more than 1 million people were called, screened, etc., thus m