Loading summary
Transcript33 lines
- [00:01]
Lisa Su
Hi, I'm Amy Bernstein, HBR's editor in chief.
- [00:04]
Adi Ignatius
And I'm Amy Gallo, a longtime contributing editor to hbr. Along with Amy B. I host our Women at Work podcast, which now releases episodes every other Monday year round.
- [00:14]
Lisa Su
That means more practical advice and more insights to make you feel seen and supported in your career.
- [00:21]
Adi Ignatius
Subscribe to Women at Work wherever you listen to podcasts. Welcome to HBR on strategy, case studies and conversations with the world's top business and management experts, hand selected to help you unlock new ways of doing business. As CEO Lisa Su has transformed AMD into one of the fastest growing semiconductor businesses in the world, she's also seen firsthand the way AI is reshaping companies and entire industries. In this conversation with adi Ignatius during HBR's 2024 Leaders who make a Difference conference, she explains how leaders can responsibly harness AI to boost their productivity and stay competitive. Her biggest piece of advice? Experiment aggressively. Sue shares what that's looked like at AMD and how your company can adopt a similar strategy.
- [01:23]
Amy Bernstein
So every conversation about AI that I have eventually evolves into something very dark. You know, that is AI an existentialist threat in some way to not just our jobs, but to, you know, our very existence? You know, I'm assuming you're a relative techno optimist, but help us out. If AI is going to be a force for good, how does that happen? Will it happen? Will technology save us from the downsides of technology? Or do we all, all of us need to be contributing to the discussion now to make sure we don't get these, you know, the sort of worst possible outcomes later?
- [02:01]
Lisa Su
Well, as you said, I'm probably a techno optimist, but I'm actually a very, very pragmatic way of thinking about this is the technology is not perfect. Okay? As good as technology is, we're still in the very early stages of the deployment, deployment of AI. And we do know that, you know, the AIs are not always right. And so part of what we have to do as a set of leaders is figure out how to use the technology for good and also protect the downsides. And look, I think this is a very vibrant conversation. I think all of us are learning in the process. You know, I will say that, you know, I've personally learned a ton over the last, you know, 12 plus months in terms of how to apply AI even within our own company, and also talking to many of my peers how things are going, and I think we all recognize that we're in a learning process but the key is to be very active in that learning. So, you know, my belief, and I know there's a lot of doomsday theories about how, you know, you know, AI is going to take over, you know, all of our jobs. You know, I actually am a subscriber to the belief that what we have to do as leaders of companies is to really learn how to harness the power of AI and, and also bring our employees along with that so that we're actually making our employees more productive and we're able to make our companies more productive, knowing that, you know, there are, you know, some areas where we have to be careful with the use of AI.
- [03:34]
Amy Bernstein
Yeah, that's helpful. You know, there's also another aspect of this which is just the, the, the balance between speed, you know, bringing products out to the market as quickly as possible. Now that there is a market versus CA that's reflected, as you said, you're learning and there's things we don't know yet about the technology. How do you think about from where you are at amd? How do you think about this balance between speed and caution?
- [03:59]
Lisa Su
Yeah, I really believe in fast experimentation and implementation. So I don't believe the answer is let's slow down. I think what we have to do is experiment. Where we've spent time is we actually have a responsible AI council. I think, you know, all of us as leaders, you know, if you're leading, you know, companies or teams, you have to think, you know, about how to utilize the technology responsibly. We think about things about, like intellectual property, you know, how to protect our intellectual property as well as protecting our customers and our partners intellectual property. But that being the case, I think the power of AI is finding those use cases that give you very, very significant return on investment. And, you know, we've seen in some of our workflows, like in some of our design workflows, we've seen what used to take, you know, weeks and months really come down to days. And when you think about how valuable that is to your enterprise, you have to really, you know, push the envelope on using the technology. And there are lots of, you know, you know, lots of, you know, people who are out there to, to help in terms of experiences. I know that, you know, it's a very active conversation whenever I'm talking to my, my peer CEOs these days in terms of, you know, what are you learning? Where are the use cases that are beneficial, you know, what are the things to be careful about? So I think this active dialogue is is really helpful.
- [05:29]
Amy Bernstein
And I'd be interested in your advice for people who, you know, when, when. Well, let's say when ChatGPT came on the market, you know, lots of people experimented with it and played around with it and you know, and, and now I don't know what wave we're on, but, you know, now it's okay. But how, how do I actually use it? How do I actually apply it in my company? You know, you mentioned health care and people often mention healthcare as a, you know, a clear use case. But that's, that's very specialized for the general audience here. What would your advice be? How do, how do people figure out, I guess there are two things. How to protect themselves against being disrupted by AI solutions. But then maybe more pertinently, how do, how do I use AI to improve my business, whether it's efficiency or something else? How do, how do you know, what's your advice for people who are even just trying to think through that problem?
- [06:21]
Lisa Su
Yeah, I would say, you know, again, look across the use cases and the workflows in your, in your business. The places where it's, you know, obvious, you know, sort of very, very near term successes can be in things, you know, called co pilots or where AI is actually a helper to someone, you know, to your employees. And you know, I think about, you know, these types of copilot exercises, whether it's, you know, on the engineering side, we're using copilots to help us design code and really write code and to help us look at test cases and use cases, improve our quality, those kinds of things. When I look at things that are more business oriented, we're looking at how we use AI in our marketing and our communications and our content creation. Again, these copilots will allow you to, let's call it, get close to the answer. And then of course, the final touches are being done by your expert employees. There are many, many cases like that through every enterprise where you can think about workflows, where you can accelerate your time to get an answer. The places where, of course, you have to be a little bit more careful are places that you would rely more on the AI itself to come up with the answer. And there you have to do a lot of testing to make sure that you get the right answers. But again, my advice is lots of pilots experimentation and then figuring out where it has the most value. You know, we've certainly seen as we've deployed AI across our business, that there are some places where, you know, very high value, very low barrier of Entry and then there are others where, you know, frankly the tasks are. You know, you have to put sort of a lot more work into making sure that the models and the AI are more adapted to your particular use case. So lots of experimentation and really looking at where you can get the most bang for the buck in the near term.
- [08:31]
Amy Bernstein
Yeah, thank you for that. Here's an audience question. This is Melissa Quillen. Not sure where Melissa is, but question is, when it comes to AI, how are you anticipating returning real time data, data mining so that you can pivot your business almost immediately to current trends or to resolve issues that pop up?
- [08:49]
Lisa Su
Yeah, absolutely. We have done, there is quite a bit of work and we've also done work ourselves on looking at things being more predictive in sales cycles and looking at some of the data that comes in to those trends. I would say that requires a bit of training on your business because not every business is different and there does need to be a bit of training on your specific data. But I do think that you can get some very nice patterns and trends that come give you insights of where to sort of dive to the next level of detail going forward.
- [09:27]
Amy Bernstein
Yep. So I want to ask you about your, you know, your run at AMD. You've been CEO now for about 10 years. You said early on that one of your goals was to bring focus to the company. How do you determine which businesses to prioritize and you know, how do you get buy in? How do you, how do you think about focus in that, in that role?
- [09:46]
Lisa Su
Yeah, so I've been at AMD about 12 years, CEO for almost 10 years. And you know, one of the things that is true in every business around the world is that you have more opportunities than you have, you know, you know, people or resources or leadership bandwidth. And so for us at amd, it was deciding really what are we going to be best at. And you know, our heritage has been one of high performance computing and really building, you know, sort of at the, at the bleeding edge of technology. And that was really, you know, our focus item. So there were some things that we had to choose not to do. Like for example, you know, mobile phones are very interesting part of semiconductors. There are lots of great companies in that area. That wasn't the perfect area for amd and we just had to really choose the things that we were best at. So our focus was high performance computing. Before, high performance computing was sexy. And now we can say between high performance computing and AI, you know, we are in perhaps one of the most exciting areas if not the most exciting area in semiconductors. And it has a lot to do with our heritage and focus.
- [10:56]
Amy Bernstein
So I know your goal is to stay at the cutting edge of technology, the next innovation. This is a competitive industry, and when you're up against big players like Nvidia, how do you do that?
- [11:09]
Lisa Su
Well, the beauty of technology, and I like to say this very much, it is about building great products. And, you know, to really do that, we actually have to kind of see the future. We need to decide, hey, where's the industry going over the next three to five years? And we need to place big bets on technology. And I think from that standpoint, it is one of those areas that is very rewarding if you make the right big bets. And we've made some very good bets. I think as we look at technology going forward, I'm super excited about what we're doing in AI. It is, you know, it's sort of a confluence of events. I mean, generative AI has come into fruition. And the fact is, you know, everybody needs AI compute technology, and we're one of the very few companies in the world that can do that. And, you know, we've been, you know, really investing in this place, in this space for the last, you know, 10 years. So it is one of those places where you have to kind of, you know, see across the horizon. And with that, we invest very heavily in R and D and the key technologies to enable the next generation of products.
- [12:18]
Amy Bernstein
I love your observation. Who knew this industry would be sexy? But you're having your moment, so that's great. So here's another audience question. This is Gajan Yogaswaran who's asking how expensive versus accessible will AI technology be in the medium term? And the point is, given the large cost of materials required for building semiconductors for employee headcount at the big producers like amd, do you see the cost of accessing this technology will limit the ability of certain people, certain companies, to take advantage of what it could offer.
- [12:50]
Lisa Su
Yeah, you know, the great thing about technology, especially when you think about usage curves, is, you know, we're very cognizant of the fact that for technology to be most broadly adopted, you do actually need to get, you know, sort of the cost to a very, very reasonable point. So, you know, one of the things that we're working on today are things like, you know, if you think about there are all kinds of large language models that are used in AI. There's some who are the most advanced, the largest which require tens of millions, hundreds of millions of dollars, maybe even billions to train. But frankly there are ways to really access more fine tuned models that don't require that kind of investment. Or if you think about how much cost to ask a question to chat or one of your co pilots these days, you know, we call that a, an inference opportunity. We're absolutely looking at reducing the cost of that by factors over the next couple of years. So I don't believe that this is going to be a, an overall issue where the cost is prohibitive. I think it is an issue of you have to decide where your return on investment is and you know, where are you going to see the largest productivity enhancements. And that is very much what we're driving as we look at advancing the technology going forward.
- [14:15]
Amy Bernstein
So your industry seems very complex and the supply chain seems very complex. On top of that you have the uncertainty of kind of political and trade issues. As I said, it's a sensitive industry. China recently said at least it was prohibiting AMD and Intel chips from government computers. Can you do anything, how do you respond to that? Can you do anything to try to move the needle on policy issues like this?
- [14:42]
Lisa Su
Well, I would start with the notion that, look, every country has to do what they believe is in the best interests of their national interests. That being said, the particular question that you have about China's policies around government procured processors, that actually wasn't new news. That was telegraphed actually late last year. And so it is something that again we are, you know, we look at sort of the breadth of the market that we have. You know, we are a global company, we work in, you know, all markets. China is a large market for us. And so, you know, within that, as long as we can plan across the different markets, I don't see it as a significant factor in the business. I think the more important conversation is, you know, we're very much about driving, you know, deep partnerships across the globe. And you know, that's with, you know, both large companies as well as small companies, startups and companies are very regionally focused and will continue to drive deep partnerships across the world.
- [15:51]
Amy Bernstein
As I mentioned at the start, you may well be the most prominent woman in the technology industry. How do you think the industry is doing now in terms of gender equity?
- [16:02]
Lisa Su
Well, that's very kind of you to say that Adi. I appreciate that. Look, I consider myself extremely, you know, lucky to be, you know, where I am. This is kind of my dream job to be a part of an industry that is, you know, so important and essential to the world. And be leading a company like amd, you know, in tech, look, there are not enough women. I mean, you know, I think we can, we can say that it's, it's one of those areas where, you know, we're consistently trying to, you know, drive more, you know, sort of more gender diversity as well as just overall diversity of thought. And the reason for that is, frankly, is, you know, we want to build the best business and we want to build the best products. And to do that, you know, you do need diversity of experiences and thoughts. You know, I'm a big believer in, you know, the best thing that we can do is give people opportunities. I was very lucky in my career and I got, you know, a chance to, you know, to really experience many things early on in my career, which helped give me some great experiences. And so that's very much what I'm focused on doing is, you know, giving women sort of more exposure to the industry overall and then, you know, opportunities to, you know, to shine and, you know, sort of demonstrate their capabilities going forward.
- [17:22]
Amy Bernstein
So there's also the question of, I guess, age diversity. David Dawson, a viewer asks, do you see any clear opportunities or gaps where new perspectives and, you know, I think by that he means new graduates, young workers will be beneficial and let's say, particularly in AI.
- [17:38]
Lisa Su
Yeah, look, we are always looking for new talent. I mean, we've significantly grown as a company. When I first started as CEO, we were about 8,000 people. We're now about north of 25,000. So lots of growth over the last 10 years. And I think the key for that is a diversity of perspective is super important. And what I like to say, especially when we're looking for new graduates, we're not like, we don't view hiring somebody out of school as like job training. Like, we're not looking for that exact software skill to plug into, you know, a software team. What we're looking for is, you know, people who are great thinkers, who are great problem solvers, who are here to build a career and, you know, here to learn a lot of different things. And along the way, we're going to need your hardware skills and your software skills and, and your problem solving skills and. And so, yes, I think diversity of thought is really important. You know, we love new graduates out of school and, you know, we hire across the world that, you know, sort of, you know, new hires every, every year. And, you know, we'll continue to diversify our talent base going forward.
- [18:54]
Amy Bernstein
So you can't do an HBR interview without getting at least one classic HBR question. So here's my classic HBR question. You know, in your decade as CEO, what's the most important lesson that you've Learned in these 10 years?
- [19:06]
Lisa Su
Yeah, so I think the most important lesson that I've learned is to really be very ambitious in the long term goals that you set for a company. I mean, if you think about where we were, we were a $4 billion company in 2015 and we're now north of 22, 23 billion last year. I think setting very ambitious goals for the team while having very clear milestones for how we show progress along the way. Certainly in our business it's about long term thinking and charting a strategy for that. But everyone needs some near term milestones as well.
- [19:46]
Amy Bernstein
So there's an audience question that has gotten lots of upvotes. You can do with it whatever you want. This is from Bashar. Don't know where Bashar is from. But Bashar's question is, what are you reading now?
- [19:58]
Lisa Su
Oh, wow, that's a great question. I read a lot of things online actually, and believe it or not, I'm a, I'm a pretty avid user of both Reddit and X because they actually helped me get very good real time information of what's going on in the world.
- [20:19]
Amy Bernstein
Okay, last question. So a couple people have asked, are you using on the topic of sustainability, is AI helping AMD achieve its goals for sustainability? And then more broadly, do you see AI playing a role in influencing sustainability or CSR efforts for you or for others?
- [20:39]
Lisa Su
Yeah. Let me turn it around the other way. I mean, we are very, you know, our technology is actually very focused on sustainability. So the idea of, you know, where technology is going, think about it as not just about high performance, but it's about what performance can you get at a certain, at a certain PowerPoint. So we're all about, when you think about, you know, today's limitations, frankly, power will be a limitation, you know, as you go forward. And so we're constantly looking at, you know, how can we be more efficient with our products, which help the overall sustainability conversation. Now as it relates to. I do absolutely believe that I will help us in sustainability from the standpoint of it will get us to answers more efficiently. And with that, you need, you know, less, less power for that. That being the case, you know, there's also the reverse trend, which is we are using a lot more computing to, you know, to help us modernize our businesses. So a lot of focus on sustainability. What I would definitely say to this audience is that the newer the technology, frankly the more sustainable it is because you do have all of the benefits of newer technologies being much, much more power efficient. So you need much less power to get the job done.
- [21:58]
Amy Bernstein
Lisa, I want to thank you for being at this event. I have long admired you and long admired amd, so it's really nice to have this conversation. So thank you for being here.
- [22:09]
Lisa Su
Thank you so much for having me this morning.
- [22:16]
Adi Ignatius
That was AMD CEO Lisa Su in conversation with HBR Editor at Large Adi Ignatius. We'll be back next Wednesday with another handpicked conversation about business strategy from Harvard Business Review. If you found this episode helpful, share it with your friends and colleagues and follow our show on Apple Podcasts, Spotify or wherever you get your podcasts. While you're there, be sure to leave us a review. And when you're ready for more podcasts, articles, case studies, books and videos with the world's top business and management experts, you'll find it all@hbr.org this episode was produced by Dave Diulio, Ellie Honaine, Terry Cole, Julia Butler and me, Hannah Bates. Kurt Nickish is our editor. Special thanks to Ian Fox, Maureen Hoch, Erica Truxler, Ramsey Kabaz, Nicole Smith, Ann Bartholomew and you, our listener. See you next. Strategic growth isn't just about where you're going, it's about where you build. Global business leaders are choosing Ohio for its pro business climate, rapid innovation and tailored incentive packages. With Jobs Ohio, you'll find a partner that moves on your timeline, helping you scale with confidence. Make your smartest move yet. Get started@jobsohio.com.