Forty percent of HR leaders believe artificial intelligence will help fill the skills gap. That’s according to a new study by Learning House and Future Workplace, which surveyed 600 U.S. HR leaders.
More than half of those surveyed acknowledged the skills gap and more than a third believe it’s harder to fill open positions now than it was in 2017, but some critics say companies are not doing much to fix the problem. The study found that 74 percent of companies are only investing $500 per employee on learning and development.
Jeremy Walsh, senior vice president of enterprise learning solutions at Learning House, said he was shocked by the low amount of money being spent on L&D. “It’s just ridiculous to see that amount of money being spent,” he said. “I think we will start to see a shift in how much they’re willing to invest in skilling and reskilling.”
Walsh did note that while $500 was the average amount spent among all companies, the larger companies spent more — closer to an average of $1,500 per employee. Further, more than half of employers noted a lack of budget as their most significant obstacle to upskilling employees.
“It takes a lot of time and money to fix the problem,” said Dan Schawbel, research director at Future Workplace. “Companies are moving very fast, and they may believe they have other priorities right now.” Instead of investing money on reskilling current employees, Schawbel said companies would rather just outsource the jobs or invest in AI. Indeed, 40 percent seem confident in AI.
“When people see a stat like that, our immediate posture as human beings — none of us want to be replaced by a machine — is thinking, ‘Wow, 40 percent of HR people think we’re going to be replaced,’” Walsh said. “But that’s not really what it’s saying. It’s saying it’s going to help us do a better job of finding the right people for the right jobs.”
At some level, this is already happening. Walsh pointed to LinkedIn algorithms that help recruiters find people with the right skills to match them with employment opportunities.
Walsh said one reason for the 40 percent finding is that companies want to invest in AI because they know it will become more stable and usable. “They realize it’s going to change the jobs that people need to do,” he said. “And so the idea of training a bunch of people for jobs that don’t exist — that’s hard.”
Schawbel said AI is also appealing because machines can work longer hours without requiring employee benefits or compensation. “They can also increase efficiencies that will enable organizations to grow without adding additional headcount,” he said.
For example, the average wage of a Starbucks barista is almost $20,000 per year, while a robot designed to make 120 cups of coffee per hour costs $25,000. “Robots can work seven days a week, you don’t have to pay the robot overtime and there’s no employee benefits,” Schawbel said. “So even at the basic level, if robots can do things more efficiently, it saves a company money.”
While coffee making may be a fairly trainable skill, some skills are more dynamic. Google Brain, for example, is a deep learning AI research team at Google that has been focusing on using AI to build software that can design machine learning software.
Walsh said that frees up the data scientists from hours of coding to focus on developing more sophisticated models and better applications of how to use the software. “It just takes the work that they’re doing to a higher level versus kind of punching the keys, which is what a lot of data scientists end up doing right now,” Walsh said. “They’re so ingrained into building the machine that they can’t think about how the machine is being applied.”
AI is changing marketing too, as it can already send emails, schedule posts and analyze data. A Forbes article reported that this is forcing marketers to be “technology gurus with a depth of social and emotional intelligence to complement their abilities.”
Schawbel said AI is still in its infancy so it’s hard to tell what the long-term productivity and labor impact will be, but there are estimates that it could cause a 35 percent growth in productivity.
Necessity or Choice?
Schawbel noted that since companies aren’t investing enough in employee training and thus don’t have the right pool of candidates, it might be out of necessity — not choice — that they are using AI in this manner.
Walsh, on the other hand, said companies that are constantly looking toward the future are going to adopt AI regardless. “Because many believe that AI is going to play a huge part in improving efficiency and improving a company’s ability to compete and meet customer demand, they’re naturally inclined to be investing in AI anyway,” he said. But he said the compounding pressure of fewer “work-ready” candidates — people who understand the exact skills needed in today’s workforce —is probably also expediting the adoption of AI.
Schawbel said this issue comes with its own implications, such as bugs, privacy issues, complaints and, most important, a lack of training for current employees in using AI. Schawbel said this dilemma could create a different skills gap scenario, where employees that retain their jobs are not going to be able to work with AI because of a lack of training. “You have to learn how to use these tools and machines, otherwise you’re going to be irrelevant too,” Schawbel said. “There’s going to be a training cost either way.”
Walsh said everyone is trying to wrap their heads around what the jobs of the future look like and one way to get ahead is to train employees to be digitally fluent in AI and machine learning. “The more comfortable we can get people with those concepts and get them fluent with working with those types of AI bots, the better and more efficient we’re going to be,” he said.
Schawbel and Walsh agreed the skills gap isn’t going away any time soon, as jobs and skills are constantly changing and technology is speeding up.
“We’re going to see more collaboration between educators, between companies and between the government to step in and provide training options to reskill and upskill individuals, for those whose jobs are going to either be eliminated or enhanced by AI,” Walsh said.Filed under: TechnologyTagged with: AI, artificial intelligence, Deep learning, Future Workplace, Google Brain, Learning House, machine learning, reskilling, skilling, skills gap