AI Recruiting Tech is Blowing Up. But Where Are the Recruiters Staffing for AI?

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Lionseye insights from AC Lion

This article was penned by Alan Cutter, Founder and CEO of AC Lion and Lionseye Group.

I can’t go a day without reading another article about AI recruiting tech or getting another email from an AI startup pitching their product. Some of them are interesting, chatbots streamlining the process of screening candidates, data-driven systems who calculate the exact right time to reach out and bias free filter systems. Others, the all-in-one “smart-recruiters,” are ambitious but are a few years short of going from science fiction to science fact.

The growth in artificial intelligence technology in our field has become such a major talking point among recruiters that we have forgot to ask the most important question, who is building out these AI teams?

Over $650 million dollars in talent acquisition efforts in 2016 for just AI roles was spent by Amazon, Google, Microsoft, Nvidia, Rocketfuel and many more of the major players in tech and enterprise.Startups with AI as their core product acquired over $5 billion in funding. In a time when AI-focused companies and staffing is one of the fastest growing areas in high-tech, it is pivotal for recruiters to break into the scene. But for many, even recruiters with extensive backgrounds in digital and technology, the hurdles to jump in locating talent in an emerging industry are foreboding to many in our space.

Recently I, along with other like-minded innovators, have founded ImagineIT.ai, an initiative dedicated to fostering artificial intelligence focused conversations among industry leaders. With our inaugural roundtable, the major names in artificial intelligence from Facebook to Clarifai came together to discuss the issues involved with building artificial intelligence divisions, investing within AI and business models in the current landscape.

 

 

What Companies Should Be Looking For

For the businesses who want to invest heavily in their artificial intelligence initiatives, it is not a matter of just hiring a Chief Innovation Officer or savvy young tech genius to come in, shake things up and then leave to find their own startup. Companies, from enterprise to VC-backed startup, need to understand the pipeline of their business model and where artificial intelligence is applicable within that pipeline. Vendors within the AI space must also follow suit. “I see hundreds of business models,” says Global Director of Emerging Tech Partnerships & Investments for Thomson Reuters, Joyce J. Shen “and about 80% of them are complete crap.” Any company looking to innovate with AI needs to understand their business model with AI and then can go about building out their team. AI isn’t the business model: it should make your core business better.

 

Who Companies Should Be Looking For

In 2013, Amazon, Microsoft, Google and Facebook all offered high paying positions to one candidate, Matthew Zeiler, a PhD student coming out of NYU’s “Deep Learning” program. Mark Zuckerberg even flew out to meet with Matthew before his graduation. A heavily tapped source of talent is being fostered within machine learning and artificial intelligence masters and PhD programs in schools like Carnegie Mellon, Stanford, NYU and UC Berkley. Outside of these tech hubs, data scientists, developers and programmers all have the skillsets required to transition into an artificial intelligence focused position. According to machine vision engineer, Boris Babenko, the greatest candidates are those with open-source projects under their belt and the creative drive to innovate a new field.

 

Matthew Zeiler and Matt Turck. Image Courtesy of Data Driven NYC 

Understanding AI Beyond the Keywords

If you had asked me, or anyone working in tech or digital recruiting, about “machine learning,” “image recognition,” or “computational biology” a couple years ago, you would get back a lot of blank stares and head scratching. Now in 2017, the jargon of yesteryears are the real technology trends that are shaping businesses and industries. While some recruiters think they can get away with just knowing AI “buzzwords,” when talking to clients and candidates, many will soon learn that there is no getting around truly knowing the space. 

Here are a few skill’s you’ll really want to have a firm grasp on before you even think about talking to a serious candidate or client about AI.

  • Deep Learning
  • Image Recognition
  • Data Mining
  • Algorithms
  • Neural Networks

 

These are pioneering, cutting edge candidates that are used to being cultivated.  They are going to want to go to a company that gets them—and the AI space. 

 

Conclusion

We are in the wild west of artificial intelligence as an industry and a business solution. Industry leaders want to get the conversation started on how to implement AI successfully into their businesses. Those working directly with AI technology want everyone to be on the same page in the advancements of this tech and the implications of integrating automation. When we created ImagineIt.ai, we went in with the mindset of creating a community of industry leaders and AI innovators to discuss the future of the most talked about emerging tech. I’d say this is a great time for us, for both recruiters, businesses and innovators, to be having these conversations.

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