The AI Skills Gap
Anyone who works in human resources for a company looking to hire will likely tell you that they face an overall talent shortage—regardless of the industry or sector they compete in. It’s simply a fact of life in a booming economy with an unemployment rate that remains near record lows. In fact, more than four in 10 businesses are worried they won’t be able to find the talent they need, according to Indeed polling; and nearly three in four employers are finding it hard to recruit relevant prospects, per TalentNow. Contributing to this quandary is the fact that the rate of labor force participation is dwindling; U.S. Census and Bureau of Labor data shows that the percentage of eligible U.S. workers is expected to fall to approximately 61% by 2026 (down from about 67% in the late 1990s), partially due to lots of baby boomer retirements.
But candidates who possess aptitudes related to artificial intelligence (AI) or machine learning (ML) appear to be in particularly short supply. LinkedIn’s “2018 U.S. Emerging Jobs Report” reveals that six of 15 emerging jobs are associated with AI in some way, and AI skills—which experienced a 190% increase worldwide between 2015 and 2017—are among the fastest-growing on LinkedIn. Yet three in 10 executives are concerned that they’ll be unable to meet the growing demand for AI abilities over the next few years, per PwC.
Worse, Diffbot’s “State of Machine Learning Report 2018” indicates that, worldwide, only roughly 720,000 people have ML skills—that’s only 0.009% of the planet’s population (fortunately for the United States, 30.8% of this global talent pool, representing nearly 222,000 workers, reside in America). And 56% of senior AI professionals feel the dearth of qualified AI experts is the single largest impediment to AI implementation across business operations, based on a recent Ernst & Young survey.
Whether you’re seeking to hire an AI/ML pro, or vet vendors and prospective partners that rely on them to succeed, it’s important to understand the cause and effect of the skills scarcity, the proficiencies and positions most in demand, and the best ways to recruit and retain these specialists.
Factors Behind the Shortage
Ask [24]7.ai’s chief data scientist Cosimo Spera and he’ll tell you that businesses large and small want to get a slice of the AI/ML talent pie before it’s all carved up. “Virtually every company today wants to play in the AI/ML sector and chatbot space, even though they are in very early stages,” he says. “But most professionals have not yet figured out exactly what they want to do.”
Alan Majer, CEO of Good Robot, says this is a simple case of demand overpowering supply at a key time. “There’s a large call for artificial intelligence, due to what’s seen as a growing multibillion-dollar market for consumer AI in areas like voice assistants, as well as opportunities to use AI to reduce costs or create value. With such rapid growth, the workforce simply can’t expand fast enough to meet that demand,” says Majer.
Shlomit Yanisky Ravid, a visiting professor of law at Fordham University Law School who teaches courses on AI, believes the recent revolution in neural networks has also contributed to a burgeoning industry that’s nevertheless bereft of sufficient talent. “There have been such rapid developments in AI software and networks, and it’s all happened primarily in the last three years,” she says.
As a result, “many companies are not prepared and they now realize they need experienced staff,” adds Ravid.
Many believe the problem isn’t merely a lack of available AI/ML professionals; it’s also that not enough of these people have the right AI/ML skills. “A lot of these areas are so new that it’s hard to say what constitutes being an ‘expert.’ There’s also a lot of confusion about what expertise is needed,” Majer says. “Do you need a data scientist, a machine learning expert, someone with experience in existing toolsets, or someone with business/domain expertise who knows how to harness AI to solve problems? In the race for talent, many companies go out looking for one skill set but actually need another.”
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