Ethan Mollick is considered one of the leading experts on the emerging world of generative AI, jobs and the economy, but you might not think so if you take his word for it.
“Leiden is not as far as an expert,” he told CNBC's Sharon Epperson at the CNBC Workforce Executive Council Summit in New York City on Tuesday.
The professor at the University of Pennsylvania's Wharton School, who says he has advised everyone from Federal Reserve Chairman Jerome Powell to Jimmy Fallon on the new world of gene AI, shared a blunt message with HR officials attending the CNBC event. “I can tell you no one knows anything,” Mollick said.
That includes, he says, the top AI research labs when it comes to the job market and use cases. “They don't know what it's for. They tell me they're using my Twitter [X] feed to figure out use cases,” he said.
Underlying his words was a simple point: no company today can hire an employee who has five years of experience using gene AI. “They don't exist,” Mollick said.
Certainly, there is some evidence emerging of workplace productivity gains from generational AI, and Mollick and Chief Human Resources Officers at the CNBC WEC Summit shared some evidence from their research and real-world experience with employees, at companies Walmart Unpleasant VerizonAnd JPMorgan. But there was general agreement that there are more questions than answers for business leaders today when it comes to AI and the workplace.
“We honestly don't know what the future looks like,” said Claire MacIntyre, senior vice president and chief people officer of Sam's Club, in a separate Summit session with CNBC's Morgan Brennan. “This is the worst version of technology we'll ever use,” she said.
We need to move away from rewards based on having all the answers
Much of the progress in AI is taking place within a domain that technology experts describe as a 'black box'. Experts at the CNBC event said a similar gap exists today in our understanding of AI's impact on the economy, spanning from early education through professional careers.
MacIntyre said that modern career culture is based on being rewarded for 'having answers', and that this is a process that starts in the education system. But that is shifting for leadership and employees. Leadership in particular, she said, “is no longer about having answers. It's now actually about asking brilliant questions, editing information and making decisions at the speed of TikTok,” she said.
Verizon Chief Talent Officer Christina Schelling, who spoke on the same panel with the Sam's Club director, agreed. For decades, she said, “We were rewarded for perfection and for being an overachieving perfectionist in the workplace.”
But with AI, Schelling said, “the outcome is rarely perfect or the one exactly you need to move forward. It's okay to be okay with failing or being wrong,” she said. How quickly you can recover and continue to test and try new things is as likely to be the successful model as the way we have been rewarded since kindergarten, she said, even if it goes against the grain.
“What we're trying to focus on is learning less as an action and more as a mindset,” MacIntyre said. “Be curious and be able to unlearn, and be feedback-savvy.” All of this, she says, is critical to how culture should evolve.
For employers, that makes hiring more difficult, said Kiersten Barnet, executive director of the New York Jobs CEO Council, which was founded by JPMorgan Chase CEO Jamie Dimon and other CEOs of the city's largest employers. “Everyone knows we need something different than before, but we don't know what that will look like in five, 10 years,” she told CNBC's Brennan in a one-on-one interview at the Summit.
She also drew a direct line to education, a focus for her organization, which works with colleges and high schools in New York City to prepare workers for jobs that require AI skills to build solid career paths and increase earnings potential. “Think about traditional classrooms. They look the same as they did 100 years ago in the way we learn. Even if the content is different, you can't learn critical thinking from a textbook,” she said.
She noted that the New York Jobs CEO Council is involved in an effort to make gen AI a requirement for students, and OpenAI is working on certifications that she believes will quickly become embedded and incorporated into courses, ultimately leading to more work roles that need to be thought about in terms of applied uses of AI technology, but she added that it remains an “if.”
“We don't have that now and it's difficult to assess everyone's competency in the technology being applied,” she said.
What we do know about AI, workers and jobs
Barnet said she's willing to make some bets on what will work for employees in the future. First, the ability to learn flexibly and continuously is “a skill in itself,” she said.
Softer skills are more important than ever, she added, especially because of “the uncertainty of the future” and the knowledge that some skills AI can do for us.
Schelling emphasized that it has long been known that empathy, curiosity, agility and decision-making skills are all important for success, but that they will now be given more weight and factored into a more complex labor market in an AI world. It's already a data input in hiring and career development, but at the same time it's also becoming “something largely unknown or new, so the gray takes on a little more meaning,” she said.
Mollick says this logically makes sense because today's AI is much more human-like than machine-like, so people who are good with people can use it to succeed.
He also pointed to evidence from a study he collaborated on with the Boston Consulting Group that showed worker productivity significantly improved using gene AI, as well as a Procter & Gamble study that found employees performed as well as teams when assisted by AI.
“We know the impact is there,” Mollick said, but he emphasized that when it comes to job replacement fears, he sees it as a choice that leadership will make and possibly execute poorly. “I worry that organizations without imagination will think automation is the way to go,” says Mollick. And he said that in the current environment, employees will be reluctant to embrace AI if they feel that productivity gains are not coming back to them in the form of additional benefits.
Companies including Sam's Club and Verizon are already seeing results from early adoption today. At Walmart, more than 100,000 frontline workers have used gen AI over the past 18 months, including frontline managers who used ChatGPT to help them run their businesses, as well as computer vision on autonomous scrubbers that go around doing inventory counts and other mundane tasks that associates can now skip.
At Verizon, the focus is also on the frontline workers who interact directly with customers, but Schelling said the company has reached the stage of moving from pilots to “full business transformation… an AI overlay for the business.”
One of the biggest projects at Verizon was using gen AI to sift through all publicly available information about the company's more than 100,000 employees to build a better AI system to match employees with potential career paths. The company's AI was able to clean the data on roles and skills to identify career paths in the abstract, but couldn't match them to actual employees without more complete information about their lives.
“We didn't have enough data on employees,” Schelling explains. “We found that they are more likely to update external profiles than internal ones. That's why we've collected every available public piece of employee information with AI and combined it with internal employee profiles,” she said.
Employees were part of the process – although they had to log out rather than log in – and were asked to change and amend information if it was incorrect. Ultimately, Verizon went from less than 5% complete data sets to almost 100%, and this works to the employees' advantage. It offers them jobs that match their skills, as well as suggestions for training and certifications that will help plan a job they might want “ten years in the future,” Schelling said.
Although employees were initially hesitant about merging external and internal data, she says it is seen as an added value, with an attrition rate of less than 1% in the pilot group.
No. 1 consultation costs $20 per month
Mollick had three structural pillars that organizations could propose to move forward in a constructive way: developing AI in leadership, creating an AI laboratory, and making AI available to the masses.
And it's all changing very quickly. “Almost everything we knew about training people no longer applies. None of the guidance from four months ago works,” he said. “Fast engineering doesn't matter anymore. Saying the right words or being nice doesn't matter, but providing the context we give people to make decisions does matter,” Mollick said. “You need to 'crowd' the best AI users and take ideas from the crowd and turn them into products that people use right away,” he added.
And according to Mollick, there is only one way to start. “My No. 1 piece of advice is to pay $20 a month [Anthropic’s] Claude or [OpenAI’s] GPT or [Google’s] Gemini and use it for anything you can legally use it for.”
Mollick says he needs to use AI at least 10 hours a week. “It's not that hard,” he said, and you'll quickly learn what it's good at and what it's not good at. “You can't suppress it. You have to use it yourself as a leader. You can't say you're making time for it,” he added.
He said leadership should not continue to rely on the AI task forces created in 2023, calling these early leadership efforts “a portentous thing.”
“They tell you what not to do,” he said, giving the example of a large company he knows that has 780 application lines and approves one application a week. “That's not going well,” Mollick said. “It is an impasse that must be broken,” he added.
As for all the vendors selling tools, he says most just resell GPT, Gemini or Claude and don't have better access to AI than anyone else. “I can't tell you and no one can tell you unless your lab tries,” he said.
“Let everyone 'do it' and some people will be good right away and they will become the laboratory and the innovation,” Mollick said. “Waiting for answers or leaving it to IT are the biggest mistakes HR leaders can make,” he added. “Once you turn them into tools, you can think of use cases.”
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