Remember the first time you saw The Matrix? Didn’t it seem like AI was some sort of futuristic semi-frightening technology, but at the same time so far from reality that you never really thought about it outside the silver screen?
Somewhere along the way, AI shifted from science fiction to reality. We depend on AI technology to get things done every day, and many times we don’t even notice it.
All employers, large and small, are competing to attract and retain employees for the same hard-to-fill jobs in today’s highly competitive, candidate-driven marketplace.
McKinsey & Company reports that more than three- quarters of Fortune 500 CEOs do not believe their companies are effective at attracting highly talented people. Of those CEOs who do consider their companies successful at attracting top talent, only 7% believe they are effective in retaining them.
In Part 1 of this blog story I urged professional sourcers to adapt their focus as machine learning and artificial intelligence (AI) play in increasing role in the field. In a nutshell, AI can now do many sourcing activities better and faster than humans. However, there are still important things that humans do better than machines. Sourcers who focus on those things will continue to be in demand, while those who don't adapt may be edged out.
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Artificial intelligence (AI) and machine learning are changing the sourcing game, and smart sourcers are adapting. In our quest to stay cutting edge, my team implemented a few new practices discussed at SourceCon, and in this two-part blog I want to share some of those methods. You probably know that AI and machine learning are already a part of our lives. That's how companies like Netflix and Amazon learn your preferences so they can make suggestions. If you use Siri, Google Assistant or Alexa, you interact with machine learning regularly.
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