How to Lead and Reskill in the Age of AI
[MUSIC PLAYING] ADI IGNATIUS: Welcome to Harvard Business Review's The New World of Work. I am Adi Ignatius, Editor in Chief of Harvard Business Review. Each week on this show, I interview a CEO, a thought leader, or someone who can inspire and educate us on the changing dynamics of the workplace. Our viewers come from all over the world.
They work at everything from Fortune 500 corporations to fledgling startups, from family businesses to nonprofits. The aim of this show is to provide insights for everyone as they navigate this transitional moment in how we organize ourselves in the business world. So in today's episode, we have another great guest, Raffaella Sadun, a professor at Harvard Business School. I'll come back with a proper introduction for her in just a moment. But first, let's hear from our good friends at KPMG, who are our sponsors for this season of The New World at Work.
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And remember, you can watch previous episodes of this show on YouTube or right here on LinkedIn and Facebook. So my guest this week is Raffaella Sadun, a professor at Harvard Business School who specializes in questions of strategy. Her research focuses on the managerial and organizational drivers of productivity and growth.
She's the co-author of an upcoming article in Harvard Business Review entitled "Reskilling in the Age of AI," and we'll be talking about that and other topics today. Raffaella, welcome. RAFFAELLA SADUN: Thank you so much.
It's a pleasure being here. ADI IGNATIUS: All right. Well, let's get right into it. So I do want to talk about this article that you have coming up in HBR on reskilling in the age of AI.
Let's start at a high altitude. How dramatically do you think workplaces will be transformed as AI technologies take hold? RAFFAELLA SADUN: I think it's important to distinguish between what's the potential impact of this technology and what the reality will be. The potential is-- the answer to your question is very high. There will be-- as we've learned from past technological transformation, the possibility is that these technologies will change occupations radically, and in fact, there are several estimates that tell us that maybe a huge percentage of the US-- of the US population will be affected, for example, by-- occupations will be affected by these technologies. What's very interesting about AI in particular is that they have the potential of having an impact on white collar jobs and high-skilled jobs, which typically have been sort of insulated from past technological revolutions. I think the part where we come back to the reality is that, at the end of the day, what happens will be a function of the adoption process, and the adoption process is, as we know, typically very messy, as we've seen in other technological revolutions.
It depends on figuring out how to integrate these technologies in the workflow, and it depends also on the incentives to adopt, whether people will accept these technologies as their companions every day in their work. From what we know from past technological revolutions, it can take a while, and it's going to be a bumpy ride, I think, before we can really think about the revolutionary impact that is often mentioned in the press. ADI IGNATIUS: So I know you can't possibly know the answer to this, but I'm interested in your thoughts. Even the technology industry is split as to whether the widespread adoption of AI, generative AI, you name it will eliminate jobs or will somehow create new jobs as we collaborate with machines. Do you have a view on that as you're starting to see this play out in companies whether this is a net creator of jobs, subtracter of jobs? What's your guess? RAFFAELLA SADUN: I think that is the million-dollar question.
What's going to happen at the end of the day depends on what firm strategies and firm organizational responses to these technologies are. So let's first say that not every firm will be actually adopting these technologies. We've seen it-- again, we've seen it in the past. There will be a lot of heterogeneity. And those that do have basically two ways of reacting to the technology-- to the adoption-- shaping the technology adoption. One will be the lazy way, and this is people like Daron Acemoglu, who have talked about this in other outlets, where, essentially, they're going to substitute whatever workforce they can with new technologies without really changing their production processes, their organizational processes.
That would be potentially complicated. There would be elimination of jobs without really the creation of new opportunities. And then there is a second pathway that I find very exciting.
Not everybody will get there. But I am pretty certain that some firms already are rethinking their workflows, and they're rethinking their organizational processes in such a way that these technologies create new tasks and new opportunities and potentially also new jobs. So coming back to the answer-- the question-- I'm sorry to give you an answer that is not definitive, is "it depends," but the critical point is that it depends on what firms do.
There is nothing that is predetermined at this point. ADI IGNATIUS: OK, so let's get back to the reskilling question, and let's talk first from the perspective of managers. How should we think about our workforces? Are we essentially now competing for external tech talent that is skilled in these new technologies? Or can we plausibly think about retraining an existing workforce to handle this challenge? RAFFAELLA SADUN: Look, in practice, firms are constantly doing both things at the same time. They are sourcing talent from external labor markets, and I think to various degrees of commitment and resources they're also investing in training. What's interesting is that the external workforce option becomes a little bit tricky these days for a couple of reasons.
Some are related to the tightness of labor markets, which make sourcing external talent more costly, but I think also, specifically, to AI and these new technologies is the fact that these technologies are effective only to the extent that they are very integrated and well-integrated with the specific use case. And it's not clear that somebody who is hired from the external labor market who doesn't really know the production process would be best placed to adopt these technologies in the specific workflow of their organization. So these two things, one, the cost, and the second also, the benefits of having external talent, are somewhat changing. That creates-- and that's what we've seen and what we document in the article-- a newer attention towards solutions that are much more focused on internal talent and in particular, not just upskilling internal talent but also reskilling, which means giving them training that allows the workforce to jump from one occupation to the other. ADI IGNATIUS: My guest today is Raffaella Sadun. If you have questions for her, put them into the chat.
I'll try to get to as many audience questions as possible later. Generative AI is a piece of this puzzle. It's got us thinking, as a media company, as a learning company, how it creates opportunities, how it disrupts us. I figure that's playing out through-- I don't most-- companies now. Do you think we even know what the use cases are, let alone how to adapt our workforce to what those may be? Do you think we-- like, what percentage are we in terms of understanding this new technology and the potential it has to contribute to productivity or any other positive aspect of business? RAFFAELLA SADUN: I think it's very early stage, to be honest. There is the-- the estimates that I was mentioning before of this potential transformational effect of AI on occupations and jobs are typically based on taxonomies of occupations where you can break down an occupation in multiple tasks.
And then there is an inference that says, well, these tasks seem to be amenable to AI, and this doesn't. And that's how we come up with these very large estimates of the potential impact of the technologies. Now, when it comes to the reality, of course, even if an occupation is the same in principle, it can be very different across different firms. And one of my favorite example-- I have a student here in my executive program that told me how he adopted AI in this shoe manufacturing company, and you can-- I won't get into the details of what he did, but he really thought for two years about the specifics of the production process in his firm and then modeled the AI adoption based on what he was doing and what was needed. I think that this is a case where we're not talking about just getting a computer out of the box and plugging it. There will be a lot of adaptation, and this is what makes every prediction, I think, extremely reliable at this point.
ADI IGNATIUS: So I think you said before that on the one hand managers are going to be looking for talent that's out there and on the other are going to need to reskill their own workforces. So let's talk about internal reskilling. How does a how does a leader create a reskilling program that works? And are there takeaways from companies that you've seen who seem to be doing this effectively? RAFFAELLA SADUN: So that's really the motivating question for the article that we just published.
There is a lot of enthusiasm, I think, at a high level about reskilling, and we've heard with companies that truly believe in the opportunity of providing their workforce with training that really allows them to thrive in this era of technological changes. The reality, however, is a little bit different from the hype, and this is something that we are currently studying. The problem is that even a well-designed training program, what we heard from companies, sometimes has really low take-up rates. So there seems to be resistance from the perspective of the employees in putting themselves, if you like, in the mix and trying to-- going through these training programs to change occupations.
And also, what I found really interesting is there is also resistance at middle managerial levels, and so we've heard, for example, of middle managers that were very concerned of sending their own workers to get trained and especially trained to change occupation very naturally because that's how you lose your talent. If you send your workers to a training program, effectively you are not only losing the person while this person studies or gets trained, but you're also potentially losing talent in the long run. And so this is just to say what we hear at the high level, what we-- the very ambitious estimates of what reskilling can do from our interviews appear to face a reality that is often quite different.
And these are the challenges that we discuss-- that we discuss in the article. ADI IGNATIUS: So I want to stick with that because sending your team, your high potentials, whatever to learn new skills, to go off and do an executive education program, you always run that risk that you may be training them for the next job. I don't know if AI is just another example of that or somehow a more dramatic problem, but I think it might be useful for people to hear. So how do you-- what kind of incentives or what kind of programs can you set up where you do the training but you're not simply preparing your employee to go work somewhere else where they'll be in demand? RAFFAELLA SADUN: Look, that is a risk that always exists, and the organization that we spoke with embraced that risk. And so I want to say, if you live in fear that training is going to immediately make you lose your talent, that is probably not the best attitude to invest in these training programs. I think what we've seen and what seems to-- at least from what we heard, seems to work better are training programs that are, first of all, embedded in a company strategy.
And so if you are able to articulate why going through a reskilling or even an upskilling program matters for the organization and what are the rewards that people are going to get out of these training programs within the firm, that already changes the salience of the training program and how people see themselves within the organization. So I think this is one. The second one is making sure that for people that go through these training programs, they can see the benefits of training on their own skin. So I think it's interesting. Sometimes we have these super well-designed programs, wonderful technology, but you don't-- people don't know what's going to happen to their own career. Here we're talking really at the personal level.
What happens to me if I get trained and maybe I change occupation down the line? What is my career pathway? That clarity is often absent, and I think that is something that makes-- first of all, increases the chances of take-up and makes the training program more successful, not just in general but within the firm. ADI IGNATIUS: So I want to-- I want to go to an audience question now, and this is sort of definitional to provide some context as we have this discussion. This is from Olivier in Switzerland who's really asking, can you be more clear? Like, what kind of AI are we talking about here? There's AI, and there's AI, and there's gen AI, and what do you have in mind when we're talking broadly about AI? RAFFAELLA SADUN: Yeah, so in the case-- I think this is actually the question.
When people talk about AI, there is this very broad definition. In my specific-- in the specific examples that I was mentioning before, I'm thinking about, for example, decision support systems. And one concrete example would be AI use in the context of buying decisions for supply chain managers, for example. Another case could be decision support systems for clinicians, for physicians.
These are types of technologies that can help-- can help in decision-making. But then, of course, the type of applications that are there right now are much wider than that and much broader than that. ADI IGNATIUS: On generative AI, the ChatGPTs and Bard and Bing and things like that, I'm curious, are you finding a use for that in your world, in your profession, or even for your hobbies? Are you finding a use case for yourself for gen AI? RAFFAELLA SADUN: Absolutely, absolutely.
And in fact, I'm an economist by training, and machine learning has gradually permeated even what we do at an academic level. The type of information that we can now distill from unstructured data is just incredible with large language models. And in fact, Adi, with colleagues we actually digitized the Harvard Business Review archives, and thanks to this algorithm, we were able to extract the type of topics and problems that HBR worked with throughout the course of this-- throughout the course of its history. And this is just one example of things that-- again, the structuring of unstructured information I think is a very immediate application of AI within my specific field of research. ADI IGNATIUS: Yeah, great.
OK, so back to reskilling-- and now let's talk about the employee perspective. So we all know that new technologies come. People learn at different rates. You just have to expect that and figure out how to bring more people along.
Not everyone will get there. But for employees who sort of want to get there and feel like, OK, I'm late out of the gate, I don't really understand AI, I don't understand generative AI, how do-- you know, how do they prepare themselves for this transforming world? RAFFAELLA SADUN: OK, so let's first clarify that learning a new skill is scary. So I don't know-- I don't know the last time that you learn a new software, for example, or a new way of doing things.
I can tell you that, especially as an adult, it's not the easiest thing to do, even harder if this is learning a new skill to get to a new occupation. I am an applied economist. If you ask me to become a market economist tomorrow, I'd be kind of scared, to be honest.
It's hard. So I think that the first thing is getting into-- besides the obvious, which is choosing training programs that are high quality. There is such a-- so much noise right now in the training market.
That's actually a challenge, so a little bit of due diligence clearly on what you do. But I think that most of the work is actually on the mindset that you have as you approach this new-- as you approach learning new skills, and in particular, I think what matters is understanding-- trying to put yourself in a condition in which that you are going to face some sort of-- maybe moments of fear or moments of, I just cannot do this, it's too much. How about thinking about cohort models where you are not alone in this learning process, learning in the flow of work? These are all things that are able-- and that's what we heard also from the companies-- to lower the frictions and the inevitable bumps in the road that you will find when you start learning a new skill as an adult. ADI IGNATIUS: So a few questions have come in that sort of build on this question of fear, and you started to talk about just now about the broad cohorts.
But this is a question from Donna from Alabama in the US, and it's really, what else then beyond that can businesses do to communicate-- just to appreciate, yes, there's uncertainty, yes, there's fear, but to help employees move along the path despite all of that. RAFFAELLA SADUN: I think if we go back here to the importance of having clear strategic vision on how these training program fit within the company's future and the future of the employees that, to me, can really go a long way towards alleviating some of the concerns and some of the uncertainty that employees face. Why are we learning it? And what is a strategic imperative that is driving these investments in training? I think this really matters. The second one is, are you structuring the incentives and the responsibilities in the organization in a way that makes training not just an HR initiative that lives in its own silo but it's really embedded in the fabric and organizational fabric of the firm? And for example, some of the companies that we speak with make training part of the managerial responsibilities. There are KPIs around not only how much you train yourself but also how much your subordinates get trained. And these are all things that help with the alignment.
And then, as I said before, I think it's really, really important to acknowledge that there is risk on the employee side and making sure that training is as frictionless as possible. That comes with, for example, making sure that people are paid or they're not just expected to get trained on Sundays or Saturdays, making sure that they have a clear career pathway, making sure that the incentives are aligned for today and the long run. ADI IGNATIUS: So I have a question from Richard in Cape Town, South Africa, and it's about company culture.
So as we bring in AI, as we integrate AI, how do we think about maintaining, strengthening, evolving a healthy corporate culture as we're relying on machines to do more and more of what humans used to do? RAFFAELLA SADUN: I think this is a great question, actually, and to some extent, my expectation is that companies with a great culture are going to be the companies that are going to be able to make the most of new technologies, not just AI. And this is because these are the companies where change is easier. Because you have a culture, you know what you stand for, again, going back to the point of employees' perspectives, these are probably the companies where it's easier to experiment and change. Now, the other point that you're making on the extent to which companies' culture influence how the technology is used-- I think that's a really interesting one. Some of my economist colleagues are very concerned that companies' cultures are not focused enough on making sure that technologies contribute to the growth of employees rather than just a substitution.
And I think that that's a real-- there is a vast heterogeneity out there, and if you are a culture that invests in its employees, I think it's important to really think carefully about the ways in which you are presenting technologies and you're presenting opportunities for your employees to grow with the introduction of these new technologies. ADI IGNATIUS: So Raffaella, you've written in the past about the evolving needs for skills in the C-suite, and this is actually a question from Shadia in Massachusetts in the US. And it's really, what kind of leadership skills do executives need in the age of AI? So not necessarily to master AI technology, but just it is transforming-- it is and will transform the workplace. So what are the leadership skills that CEOs, that the C-suite needs most in this transformative era? RAFFAELLA SADUN: This is a question that I think pertains not just to the use of technologies but the emergence of knowledge-based and complex organizations. Since many organizations are going in this direction, the type of skills that matter are not just cognitive or strategic skills like knowing what to do or, for example, knowing in depth a specific technology.
But it's having the skill that is necessary, first of all, to combine all the knowledge that exists in your company. If you have, for example, more technically savvy people, it's your responsibility as a leader to find a way for these technically savvy people to speak to each other and communicate with the other parts of their organization that might not be as technologically savvy. So these are social skills that allow for this trading of expertise.
And then the second piece I think is also related to the soft skills, persuading and helping people cope with change. And I think that, at the end of the day, what is really difficult is to find this very unique mix of both cognitive skills and social skills. These are the type of leaders that I expect to really thrive going forward, and we actually see this already-- we see that the demand for these skills is really-- has increased a lot over the past 20 years, this combination of social and technical skills. ADI IGNATIUS: So as the editor of a magazine that writes about management issues, I've been heartened over the years to see-- you do research, and you've written pieces that say, good management actually matters. It actually contributes to higher productivity, and sometimes, oddly, we seem to undervalue the role of management.
So in the research you've done, in the writing you've done, what can managers learn from-- beyond what you just talked about from your findings to improve what they do? RAFFAELLA SADUN: Yeah, look, it's almost a definition of who I am, believing that management matters, and managers should have this clear in their mind-- they are critical for a company's performance, a company's success. So that's great. Well done, managers. Now, the piece that my research has explored in the past is that, however, sometimes even the best managers sort of underestimate the importance of basic management practices, and you want to think about complexity, you want to think about strategy, of course.
That's all really, really relevant. But please, also make sure that the basic of management-- the basics of management are implemented in your firm. In the research that you were mentioning before, we find that actually there is quite a bit of heterogeneity in the adoption of basic management practices across firms and across a variety of countries and industries and that this heterogeneity really matters for firm performance. So I think it's-- we offer different explanations of why that could be the case, but maybe starting to understand where you are and not underestimating the basics would be my advice number one. ADI IGNATIUS: So we've talked about AI in mostly positive terms, in terms of how it can contribute to a company and to its productivity. There obviously are potential downsides or actual downsides that we're seeing, and this is a question, Deborah from Ontario in Canada.
But I think there are several areas of potential concern. So Deborah's question is, thinking about the deep fakes, hallucinations, the things AI can do that are inaccurate that could set us astray, how do managers-- how do we safeguard against some of these downsides that we're already seeing? RAFFAELLA SADUN: I think that these are really relevant questions, of course. I would go back to saying that we cannot-- on the one hand, the cost of using these technologies has really decreased enormously, even over the past year. OpenAI is not even-- the wide adoption is not even a year old. So as the cost of these technologies has decreased so much, my concern is that-- and I think this is also your listener concern-- is that we would use these technologies blindly without truly understanding that they are not Oracle and they're not able to make complex judgments or the complex reasoning.
They are effectively a support system but not really a decision-maker in its own. So my advice, going back to what we were discussing earlier, is to think about the use case and never trust something that just comes out of the box. Most of the costs, I think, in the adoption of these technologies will be in adopting these technologies and truly understanding these technologies for your own specific use case. On the one hand, the costs of accessing the basic elements of the technologies have been lowered quite a bit, but on the other hand, where I think people should really focus their attention on is making sure that the adaptation is done carefully and is done in an iterative way so that you can check how-- first of all, making sure that there are no hallucinations but also making sure that you're adding value to your production process rather than just adding a new fancy toy just for the sake of it.
ADI IGNATIUS: Yeah. No, that's good advice. I do want to talk to you also about just the transformation in the workforce that's happened really because of the pandemic that caused us all to adapt. Many of us are still in a hybrid work environment.
To what extent do you think that period and what we learned from that period has permanently transformed both the workplace but also how we think about work, how we interact? What are the lasting takeaways from that moment? RAFFAELLA SADUN: Look, I think that there has been definitely a shift. We see it, for example, in job adverts that now include remote work options. I've done some work on this, and you can see that there has been definitely a big jump, especially during the pandemic months, in the extent to which companies that were not offering remote options or hybrid options now do that. Now, however-- and again, this is-- looking at the data is useful there. You also observe that there is tremendous heterogeneity across firms in the extent to which hybrid and remote jobs are being accepted in a sort of post-pandemic world.
What we are seeing is that what matters is not so much the location but is the extent to which the design of the job is complemented by other organizational choices, just to give you a few example, the documentation of work, ways of communication, ways of promoting people also, even if they're not in the office. So going back to your question, definitely one shift but also an opening up of heterogeneity I think is still playing out. ADI IGNATIUS: So having looked at technology and its effect on the workforce, I'm curious whether you are a techno-optimist or a techno-pessimist or absolutely neutral. I feel like we all make a choice as to who we are on that, and maybe it amplifies who we are inside. But I'm curious, as you've looked into some of these technologies in the workforce, are you basically optimistic, pessimistic, neutral? How do you think about that? RAFFAELLA SADUN: I am an organizational economist, so the answer that I'm going to tell you is everything will be different.
And I think what's important for your listeners is that as these new technologies emerge, what we might see and what we've seen also in the past is a polarization of outcomes across firms. My expectation is that maybe on average we won't see much or we will see something but not as dramatic, but we will see vast differences in the extent to which some firms are really able to click and figure out how to use these technologies for their own benefit. In the past, these firms have typically been quite the larger ones because there are economies of scale in technology. And then we will see other firms that just don't get it. So I would just be alert, not just on the average effects, but I would be very, very careful about this opening up between those that are at the frontier and those that remain behind. ADI IGNATIUS: Yeah.
All right, Raffaella, we're almost out of time, but I really want to thank you. Thank you for being on the show. Thank you for your thoughts.
This topic, reskilling in the age of AI, is the cover story in the latest-- the newest edition of Harvard Business Review, co-written by you. And thank you for that, and Thank you for being on the show. RAFFAELLA SADUN: Thank you so much for having me. ADI IGNATIUS: All right. Great.
So I want to thank you all for joining us today. Just a reminder, you can watch previous episodes of the show on YouTube or right here on LinkedIn and Facebook. Next week-- that's Wednesday, August 30 at 12:00 noon Eastern time-- my guest will be Arthur Brooks. He's a best-selling author and an Atlantic magazine columnist who specializes in tapping the highest levels of science and philosophy to provide people with useful strategies to live their best lives.
He is the co-author with Oprah Winfrey of the forthcoming book, Build the Life You Want-- The Art and Science of Getting Happier, so be sure to tune in next week for that. Now, if you're an HBR subscriber watching this, you can head to hbr.org/newsletters to sign up for The New World of Work newsletter where I offer an inside look each week at these interviews and talk about some of the biggest ideas that come out of them. And if you like content like this, again, why not subscribe to our magazine and website? The address is hbr.org/subscriptions. Finally, we want to thank again our friends at KPMG, who are our sponsors for this season of The New World of Work.
So thank you all for tuning in today. I'm Adi Ignatius, and this is The New World of Work. [MUSIC PLAYING]