The War for AI talent (Part 1)

If you've ever tried recruiting qualified AI talent, you know describing the process as "war" is not at all an exaggeration. As a matter of fact and according to a Gartner survey, the biggest challenge in AI is finding the right person for the job.

Why War?

Demand is through the roof (in millions!), and to say that supply is limited would be an understatement. The supply-demand ratio is even uglier for mid & senior-level roles.

This shortage of AI talent makes the competition fierce, especially for SME's who find themselves at war with companies like Google and Apple. Only the big names can afford the sky-rocketing salaries demanded by top-notch talent.

I wish I could say otherwise, but the war will not end anytime soon. Companies in all industries are starting to realize that they need AI in one realm or another, and so the demand for qualified talent will continue to grow.

Meanwhile, supply is not forecasted to increase much in the near future.

The foundation of AI is ML, and the foundation of ML is A LOT of mathematics. However, most undergrad computer science programs focus mainly on programming & not so much on maths, so the shortage of AI talent is not surprising.

Another contributor is the lack of democratization of AI, but this is starting to change. More and more universities are opening data science & AI programs. We also have growing platforms like Coursera and Udemy helping create more AI talent.

Fight Smarter Not Harder

Go-to markets like Silicon Valley are saturated, and in this digital-era, recruiting locally may not be the wisest choice. With an already limited talent pool, the last thing you want to do is limit it further.

In light of COVID-19, the world has warmed up to the idea of remote work. Recruiting globally is no longer a foreign concept. In fact, it poses a valuable opportunity for you to scale your AI team seamlessly, efficiently, and without compromising your needs.

Nathan Benaich & Ian Hogarth co-authors of the recently published stateof.ai present the challenges of gap in AI talent supply that has been ever growing from 2016 to late 2018. Much of the deep learning ML job roles have been in decrease however due to the impact of covid-19.

I founded Lyra after a) personally facing challenges in AI talent acquisition and b) realizing that there's a lot of undiscovered top-notch talent in the MEA (the Middle East & Africa).

Underrepresented talents deserve empowerment & exposure, and SME's deserve seamless access to a world-class pool of talent; That's what we believe in at Lyra and that's how we hope to help solve the global shortage of AI talent.

Always happy to support and advise; for a quick digital coffee session with me, use this link.

Other than shortage, what else makes recruiting AI talent such a challenge? How can we win the war? Stay tuned for part 2.

Sources: TechRepublic, TechCrunch, TechInAsia, Inc.,