Business leaders around the world are bullish about artificial intelligence, according to a new survey of 13,000 people in 18 different countries by Boston Consulting Group. Some 62% rank “optimism” as one of their top two sentiments, whereas only 22% rank “concern.”
Frontline workers aren’t as sure. While a promising 42% say they’re optimistic about AI, 39% say they’re concerned, indicating a significant gap between executives and the people they lead.
How can leaders close that gap? For insights, I spoke to Julia Dhar, a managing director and partner at BCG. Here are a few excerpts from that conversation, edited for length, and clarity.
JC: According to the new BCG survey, overall concern around AI has decreased since 2018. But if you look at the group of people who are most concerned about AI, it's frontline workers. I'd love to get your thoughts on that finding.
JD: Frontline workers continue to have the highest level of concern. I think that might actually be pretty understandable because you also see those same frontline workers saying, “I need upskilling.” Nearly 90% of employees say I will need upskilling to be able to cope with this changing future to be able to use AI effectively or to expand the role that I currently play in my organization or in the workforce. Only 14% of those same frontline employees say that they are getting training and upskilling from their employees. So I think that concern gap is actually completely understandable, and for leaders it creates a very clear call to action.
Number one, build a plan to train your people. Build an AI focused capability strategy. Use that to differentiate yourself from everyone else who hasn't already done so. Number two, don't ignore people's concerns. The fact that you are not as concerned as they are doesn't mitigate their concern at all. Not one bit. Talk about safety, equity, dignity at work. Participate in that conversation. And I think the third thing that leaders can do in response to that concern is to get involved in the public conversation outside of their company about what responsible regulation looks like.
JC: I recently spoke with AI-researcher Morgan Frank, who argues that technology doesn’t automate jobs wholesale. It performs tasks, which shifts the skills required to do a given job. You’ve also argued that leaders should be talking about tasks, not jobs. Can you unpack that for me?
JD: There are a lot of frontline employees sitting in companies today who probably feel a lot of fear about the disruption that is coming to their work. We do specific research on exactly that question at BCG and we call that idea change aversion—that even when we know there might be some positives that come out of the change, that we often have an allergic reaction to it. What can leaders do to overcome that change aversion? Number one, talk about tasks, not jobs. It is very clear that people are expecting that their roles will change. It's very clear that they're expecting guidance from their leaders about how to prepare.
Dhar suggests focusing company-wide communication about AI and upskilling on transparency, training, and open communication. Here’s an example of what to say that you can modify to fit your specific needs:
“Here are the tasks that we think are most likely to be quickly transformed by generative AI. We bet that you have additional ideas and places where we might also trigger that transformation and we welcome you to bring those forward as well.
The first thing we are going to do is train you for that very specific transformation, those tasks that are going to change.
And then the next thing we are going to do is open up this broader conversation inside our company about the larger shifts that are likely to happen. We're going to welcome that discussion. We're not going to avoid people's concern.”
JC: It seems like that process requires a lot of trust between employees and their employer. If a frontline employee gets an email from a higher-up, saying, “What kinds of tasks do you think this could perform?” they might think they’re being replaced. How can organizations build that trust?
JD: Before we talk about human and machine trust, we have to talk about employee-to-leader trust. If you don't have employee-to-leader trust, you have zero chance of building human-to-machine trust. One of the survey findings that should have leaders paying a lot of attention, is employees asking for more training. The gap between the optimism that leaders have towards AI and that frontline employees have towards AI—leaders have to bridge that gap before they can do any of the other things that we talked about.
What are the things that are going to help leaders do that to make this feel like an opportunity rather than for it to feel as though it is threatening? I think a big part has to start with this idea of having a genuine commitment to equitable AI, to the responsible use of AI.
But also what a phenomenal opportunity for responsible employers to come out now and early and say, “The research is very clear that most, potentially all, jobs will be very rapidly transformed by generative AI. And we are making a commitment for all of our employees today that we will upskill and prepare you for that—whether that's for the evolution of your job today or what that job evolves into over the coming years, or to prepare you for a different job.”
And what a chance, in a labor market that remains relatively tight in the United States and in many countries around the world, to say, “We think our employees, not our technologies, are the source of our advantage and we're going to lean into that.” That is one of the ways in which senior leaders, in collaboration with their HR partners, could create a sustained advantage for themselves, build trust with their employees, and frankly, I think generate a lot of trust and appreciation in the marketplace from their customers and suppliers.
HR leaders should already be developing a generative AI upskilling program for employees. Such programs take time and money, but they’re essential to gaining the trust required to actually leverage this new technology. EY, for example, has a program called EY Badges that allows any employee to select courses they want to take, and then get recognized for building skills through those courses. Dan Diasio, EY’s global artificial intelligence consulting leader, told me that his company is already working on a series of badges focused on generative AI.
It’s also important to encourage employees to experiment with generative AI tools while adhering to the guidelines your organization has put in place. Workers who have more experience with generative AI report lower levels of concern and higher levels of optimism, according to the BCG survey.
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