The first idea that likely springs to mind when you think about artificial intelligence and cars is autonomous driving. That’s certainly an important application. But the auto industry has many other uses for AI: collecting and parsing safety data, and design, to name just two. Given the hype around the opportunities presented by intelligent machines, we might expect that segment of the industry to be booming. In fact, it’s stalled.
Like a host of other industries where leaders want to explore and employ AI but can’t, there just aren’t enough people to hire.
Car companies globally aren’t progressing AI projects nearly as fast as trends suggested they would two years ago, according to a report released last month by the Research Institute of Capgemini, a global consultancy firm. This year, only 26% of auto firms surveyed were running AI pilots or proof-of-concept projects, compared to 41% the last time Capgemini asked the question in mid-2017. Roughly 10% had introduced some AI implementation at scale, but that was only a modest increase on the 7% that had done so two years ago. By other measures, progress had gone into reverse. Capgemini surveyed 500 auto executives to get its data.
The small pool of highly sought-after talent is the big issue, according to Markus Winkler, global head of automotive at Capgemini. People with specialist skills like analytics “can go to startups, they can go to technology companies, they can go to consulting companies, they can go to our automotive clients,” Winkler told Quartz, noting that there are “huge career dimensions” for talented individuals.
Across sectors, training isn’t keeping pace with job creation, compounding the problem. The specific type of talent that’s lacking includes people who are great at the algorithmic side of AI but also, crucially, those who combine that skill with other competencies, like good communication, Winkler explained. “It’s not only the maths genius that you need to find,” he said. “You also need to find the person who can articulate how to improve [a situation], how to understand and judge [it] as well.”
The auto industry is not alone. The future of work looks set to include a huge range of AI-related jobs, meaning that people entering the market now with the required skills have an array of choices. According to research by Element AI, a software company headquartered in Canada, there’s been a dramatic increase in the number of people self-identifying as having AI skills, and the number of researchers publishing on the topic, in the last couple of years.
Globally, it seems, there’s much more AI talent than there was, but it’s still not enough.
Element AI reviewed all publications submitted to the top 21 AI conferences worldwide, noting a 36% increase in people publishing on the topic since 2015. They also ran LinkedIn searches, finding that the number of people self-identifying as having skills in AI increased by 66% year-on-year. (They noted the limitation that LinkedIn data relates to what people say about themselves, rather than being a purely objective measure.) Supply of talent “does not yet come close to meeting the demand, and our survey indicates just how far we have to go given how little top talent there is out there in the world,” said JF Gagné, Element AI’s co-founder and CEO, in a release accompanying the report.
Capgemini was clear that the executives it surveyed predicted much more job creation than job loss as a result of the introduction of AI.
Then again, try telling that to the 14,000 people whose jobs were slashed by General Motors—one of America’s biggest automotive companies—in November last year. In a jargon-heavy press release GM said it was closing plants and cutting staff with a view to investing in the “future” of cars—including new technology. (The company has made clear that it wants to build a pipeline of young, diverse engineers, but it’s less clear how that encouragement relates to people already at the firm whose skills are obsolete.)
Industries—including but not limited to cars—will need to use their imagination if they’re to help workers transition, for example with targeted training, rather than laying them off in favor of a whole new cohort.
The evidence suggests that if companies don’t do so, they’re apt to get caught out trying to entice scarce workers who can pick and choose where they want to go both in terms of geography and area of interest. And that is likely to be expensive.
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