Sourcing Talent with AI – Improve your odds on the toughest talent sourcing challenge of all
Although artificial intelligence (AI) is still in its infancy, it already permeates the business world and virtually every sector now uses it – or hopes to — in some shape or form.
Companies are increasingly prioritizing their investment in AI, as well as the human talent needed to make it work, but recruitment has been a huge sticking point. “There is perhaps no other area in business where the demand for talent so far exceeds the available supply,” says talent guru John Sullivan. It’s “an ugly ratio.”
Gartner’s 2018 CIO survey further bears this out. Respondents’ biggest pain point, which was noted by nearly half, was the lack of specialized AI skills. “As such,” notes Gartner, “talent acquisition is likely to be one of the biggest barriers to AI adoption going forward.”
And just how scarce is AI talent? Like hen’s teeth, as they say, with estimates (as of this writing) ranging from about 10,000 to hundreds of thousands worldwide. The more conservative estimates, though, appear to apply only to a certain subsection of those in the field – PhDs with the optimal blend of skills and expertise. This typically consists of a background in statistics and high-level mathematics, expertise in certain programming languages, data science, and the technology tools needed to build AI systems.
Beyond this, according to TEKsystems, what’s also needed is an understanding of a company’s overall business needs and familiarity with a specific industry sector (e.g., finance or health care).
As might be expected, this doesn’t come cheap. According to figures published earlier this year, salaries can range from around $300,000 to nearly $2 million, with overall compensation packages even higher.
Even companies that can afford this, though, struggle with sourcing, which often means that those with fewer resources often struggle more. But not always. As is the case with any type of talent, successful recruitment can also depend on the company, the sector, the work itself, etc.
Improving the odds
While advice abounds on how to lure AI talent away from their current employers (as virtually none are unemployed), one of the most common recommendations is to first figure out what the organization needs and why, so that this can be articulated in the right terminology.
Also, to increase the odds of retention, says TEKsystems, companies should be sure they can provide enough work; preferably interesting, cutting edge projects, and/or those that’ll make an impact.
Other recommendations include:
- Cultivating relationships and creating a pipeline of candidates, whether or not they’re currently needed
- Getting referrals from other AI talent, and from schools with strong AI programs
- Using recruiters who specialize in AI and/or internal experts
- Becoming familiar with a prospect’s work
- Timing the offer right (for instance, when a candidate’s current employer is in the weeds)
- Using hackathons, conferences, crowdsourcing, and Kaggle competitions to identify top candidates
- Working with colleges and universities to provide referrals
- Growing your own: collaborate with colleges and universities to provide talent (recent grads) or to upskill current employees
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