Since the introduction of ChatGPT, businesses have been looking forward to the day when AI will turbocharge their workforce and transform their businesses forever. Three years later they are still waiting. why? And what’s the fix?
These two questions dominated nearly every conversation I had with executives at Davos last week, including the Business Insider roundtable I moderated with 15 chief human resources officers and other senior executives.
One explanation that came up again and again was that adoption among employees was incomplete. Many professionals are understandably concerned about how these tools will impact their work, and are at least skeptical about their usefulness, given the burgeoning development of AI. To overcome this hesitation, bosses are increasing the pressure to mandate the use of AI and incorporate it into performance reviews.
However, many executives at the roundtable opposed heavy-handed action. Cisco learned that the hard way. Francine Katsudas, the company’s chief people, policy and purpose officer, said: “By requiring employees to undergo mandatory AI training, we not only failed to promote sustainable use, but actually had some negative impact.” What worked, she explained, was “providing options.” Like when Cisco gave its engineers access to six different AI tools and allowed them to decide which ones to use and how to use them. “They loved it,” she said.
Another theory is that even if employees want They simply don’t have the skills needed to use these new tools. Some argue that part of the solution to this problem involves hiring people who are already adept at using AI. Kyle Lutnick, Cantor Fitzgerald’s executive vice chairman, said he wants to hire more graduates at a time when other companies are hiring fewer graduates. Because they can use these tools more fluently than older companies. But just hiring new talent isn’t enough. Employers will need to do more to train existing employees. “Investment is primarily in technology and less in talent,” said Elizabeth Faber, global chief people and purpose officer at Deloitte. “That needs to change.”
The third explanation was that significant productivity gains require a fundamental rethinking of how work gets done within companies. If the Googles and Amazons of the world were starting from scratch today, they almost certainly wouldn’t have the team structures, workflows, and job descriptions they have today. I think that’s why we’re seeing the AI revolution most clearly now in early-stage startups that are starting from scratch in the post-ChatGPT era.
Kyle Lutnick, executive vice president at Cantor Fitzgerald, said the company wants to hire more graduates because of their fluency with AI. lianna dahler
Faber said, “84% of business processes are left in their original state and not redesigned when AI is introduced.” “That means 16% of organizations and work processes are actually developed in an AI-native way.”
All of these proposed solutions are far from a quick fix. Encouraging employees to volunteer takes more time than threatening them with termination. It takes time to train your staff and actually get them to learn.
Job redesign will prove even more taxing. Many large companies don’t even know what their employees do on a daily basis. Building a comprehensive database of the skills employees have and the tasks they perform, and systematically identifying which of them can be delegated to AI and which cannot, is a daunting task. One chief human resources officer I spoke with said it would take years for HR to complete this process across all departments within the company.
What will these businesses look like when all this heavy lifting is done? I asked the group at the roundtable how many of them expected to have fewer employees in three to five years. 2 out of 15 people raised their hands. If it wasn’t for me, I think the number would have been higher. One of them, Gina Vargiu-Breuer, chief human resources officer at SAP, explained that the company is currently keeping its headcount flat because the business is still growing.
“But I think when you’re not growing, you have to sit here and say, ‘Okay, do we need to cut headcount?'” she said. “There are a lot of our peers in German companies who are starting to significantly reduce headcount. So this is a reality. For us, it’s not the case, because we’re growing. But I think it will be in the future.”
Even SAP? I asked.
“It’s kind of flat at the moment,” she said. “But if productivity increases but growth slows, I think we have to look at it differently.”
By the end of the weekend, I left Davos with the feeling that a workplace truly reimagined by AI, one in which companies can meaningfully operate with smaller teams, might not happen as quickly as I had hoped. That day still seems years away, considering all the hard work companies need to complete to get there.
This is something many economists expected early on, given that it is always difficult to fully integrate new technologies into the workplace. They said that in the short term things won’t change as much as we expect, but in the long term they will change much more. No matter how rapidly technology advances, humans do not change easily.
Executives around the world have come to the same realization, which is probably why I felt so frustrated at Davos. Svenja Gudell, Chief Economist at Indeed, likened the world’s urgency around AI to the impatience of parents potty training their children. “It’s a pain and a long process,” she says. “I’m like, ‘Why isn’t this happening? It’s been three weeks already.'” Her message to management was: “Give yourself some grace.”
The slower timeline is good news for the rest of us. You have time to learn new skills, discuss new public policies, and actually try to shape the future you want. But it would be a mistake to interpret the gradual changes so far as evidence that tectonic shifts are not coming. I came away from Davos convinced that when it happens, it will be much bigger than anything we can imagine now, for better or for worse.
Aki Ito I’m Business Insider’s chief correspondent.
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