Reskilling is a hot topic today, but what is it, when is it likely to happen and is it connected to the rise of generative artificial intelligence? Harvard Business Review published findings of a survey about how technology is changing what skills people need in the workplace — generative AI and big data are among the most desired skills.
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A research team at the Digital Data Design Institute at Harvard’s Digital Reskilling Lab and the BCG Henderson Institute conducted interviews with business leaders at about 40 organizations globally. They found five shifts in how training needs to be done today because of reskilling.
For knowledge workers, “many of them may well discover that (generative) AI and other new technologies have so significantly altered the nature of what they do that in effect they’re working in completely new fields,” wrote authors Jorge Tamayo, Leila Doumi, Sagar Goel, Orsolya Kovács-Ondrejkovic and Raffaella Sadun.
BCG Henderson Institute, a think tank branch of the Boston Consulting Group, found in the interviews they published in HBR that only 24% of companies directly link corporate strategy and reskilling efforts.
There are some exceptions. Companies like Mahindra & Mahindra, Wipro, Ericsson and McDonald’s have reskilling pathways built into their policies, tools and IT platforms, the researchers found. Others, like CVS, have reskilling metrics built into their performance assessments.
Doing so requires buy-in from the top brass, the researchers found. Leadership needs to make it easy for employees to reskill, and to consistently make reskilling a priority. For example, the research found that Vodaphone gives employees four days per year for personal development and learning new skills.
Ericsson, for example, has upskilled more than 15,000 people in AI and automation over three years, the researchers found.
Among organizations polled by the World Economic Forum in April, 44% of the workforce may need to be trained on new skill sets in the next five years. In the World Economic Forum’s global Future of Jobs report released in April 2023, AI was a key driver behind jobs being changed. According to the report, “Artificial intelligence … is expected to be adopted by nearly 75% of surveyed companies and is expected to lead to high churn – with 50% of organizations expecting it to create job growth and 25% expecting it to create job losses.”
Four out of five companies surveyed said they would implement learning and on-the-job training and automating processes in the next five years.
The skills that organizations considered core skills are not necessarily related to any particular technology or tools; analytical thinking, creative thinking and resilience, flexibility and agility were the top three most important core skills. AI and big data made the list at number 15, and programming was ranked at number 20.
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This report also found that AI skills aren’t important across all industries or types of work, but where they do appear they’re highly in demand. “Although [AI and big data] appears in fewer [reskilling] strategies, it tends to be a more important element when it appears,” the report said.
Plus, the ability to use AI is more in demand than computer programming, networking and cybersecurity skills, general technological literacy skills and design and user experience, the WEF found. AI and big data will account for more than 40% of the technology training programs done in the next five years, according to survey respondents from companies operating in the U.S., China, Brazil and Indonesia.
In a study of the state of generative AI adoption in 2023, McKinsey found that most organizations they surveyed that are adopting AI expect a little over 20% of employees to be reskilled. Specifically, about four in 10 respondents who have adopted AI expect more than 20% of their workforces to be reskilled.
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Perhaps unsurprisingly, organizations that were classed as AI high performers (i.e., those that derived at least 20% of their earnings before interest and taxes from AI) were more likely to reskill more than 30% of their workforces over the next three years. McKinsey noted these high performers were the exception.”Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function, suggesting that AI use remains limited in scope,” wrote authors Michael Chui, Lareina Yee, Bryce Hall, Alex Singla and Alexander Sukharevsky. “One way to interpret this is that ‘the rich are getting richer’ when it comes to extracting value from AI,” said Chui in the report.
McKinsey also found that AI has increased the amount of work that could be automated: 60% to 70%, up from 50%. That doesn’t mean entire individual roles can or will be removed, they noted. This is in contrast to the relatively small number of organizations that expect AI to replace people: just 8% of respondents say the size of their workforces will decrease by more than 2%.
Reskilling is the practice of training a worker on tasks outside their existing skill set or job description. The new skills are often related to the worker’s job title, but may be completely different. Workers may also reskill themselves if they want to change career paths.
Upskilling usually keeps the training within the scope of the employee’s current role. Upskilling may be part of promotion to a more senior role in the same career path, while reskilling may involve a different career path entirely.
“To adapt in the years ahead to the rapidly accelerating pace of technological change, companies will have to develop ways to learn – in a systematic, rigorous, experimental, and long-term way – from the many reskilling investments that are being made today,” the Digital Reskilling Lab and BCG Henderson Institute team wrote.
