The AI Skills Gap
Candidates with basic skill sets may not be difficult to find. But the ecosystem to develop them further is lacking, many agree.
“The real problem is finding the right talent with enough vertical or industry experience who are able to model business problems that can be solved by AI/ML,” says Spera. “It’s also important to nurture these professionals so that they learn how to solve different problems from across industries.”
The Classroom Conundrum
The talent deficit can also be traced to the fact that training and academic programs haven’t been able to keep up with the latest AI innovations. Consider that it was only recently that America’s first undergraduate degree in AI was offered—at Carnegie Mellon University. Yet AI/ML expertise requires more advanced degrees, the programs for which are currently lacking at institutions of higher learning.
Also, “universities have not adapted to forecasting AI growth trends; thus, any programs that teach the necessary skills have not generated a supply large enough to meet the demand,” says Tom Livne, CEO of Verbit.
To address these problems, more universities are trying to develop new curricula and new courses in AL/ML, with the aim of preparing more talent equipped to support the AI revolution, explains Houwei Cao, assistant professor of computer science at New York Institute of Technology.
“But we need to start offering introductory classes on AI as early as middle school and try to give kids a conceptual understanding of AI technology and its applications,” Cao says. “It’s very important to introduce young generations to an emerging technology that will greatly impact their future.”
Adding to the educational challenge is the fact that there’s a faculty failure, too. “Capacity to learn AI largely depends on universities’ ability to fund and retain professors over decades. And professors who can’t get their work funded tend to drop out of AI-related programs. Today, top academics are getting scooped up by industry players for sometimes seven-figure salaries,” says Kristian Simsarian, professor and founder of Collective Creativity LLC, as well as a human-robot collaboration expert who focuses on AI policy and innovation.
“Without professors, there is no capacity to teach,” adds Simsarian. “And those left teaching are not always on the technology forefront.”
Feeling the Impact
The inability to find folks with the right AI/ML repertoire can have dramatic consequences for a company that lags behind its rivals—depending on its technological aims and ambitions to compete in this space.
“When you are late to the table, you miss out on the good food. Similarly, companies that have been late to recognize the potential of AI and ML are struggling to identify and hire the right talent,” notes Spera. “For example, we’ve heard a lot about Microsoft—which has been late to the AI game—trying to recruit engineers from Google. That’s fine for Microsoft, but most companies do not have these kinds of resources to poach talent. Hence, they lose a competitive advantage.”
Some believe that startups are the most vulnerable to this problem. “Many startups fail because they cannot find qualified talent or an adequate team,” Cao says.
Another consequence of the AI/ML talent shortfall will be overreliance on inferior professionals, thereby stifling innovation. “The biggest impact will be a lot of shoddy AI. People will end up with the wrong kind of talent and produce substandard products that fail to meet the hype or expectations,” Majer says.
Jobs and Skills That Are All the Rage
Among the AI-related positions that are often highest in demand, based on Indeed.com data, are predictive modelers, machine learning engineers, data scientists, corporate analytics managers, information strategy managers, computational linguists, and computer vision engineers.
“Engineers and data scientists who can design and develop machine learning models or systems, implement ML algorithms, and collect, clean, analyze, and make business decisions based on data are the positions most in need of being filled,” says Cao.
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