HANNAH BATES: Welcome to HBR On Technique—case research and conversations with the world’s high enterprise and administration specialists, hand-selected that will help you unlock new methods of doing enterprise.
As CEO, Lisa Su has remodeled AMD into one of many quickest rising semiconductor companies on this planet. She has additionally seen firsthand the way in which AI is reshaping corporations and whole industries. On this dialog with Adi Ignatius throughout HBR’s 2024 Leaders Who Make a Distinction convention, she explains how leaders can responsibly harness AI to spice up their productiveness—and keep aggressive. Her largest piece of recommendation? Experiment aggressively. Su shares what that’s seemed like at AMD, and the way your organization can undertake the same technique.
ADI IGNATIUS: So each dialog about AI that I’ve finally evolves into one thing very darkish that’s ai an existentialist menace in a roundabout way to not simply our jobs, however to our very existence. I’m assuming you’re a relative techno optimist, however assist us out if AI goes to be a pressure for good, how does that occur? Will it occur? Will expertise save us from the draw back of expertise, or will we, all of us must be contributing to the dialogue now to verify we don’t get the worst attainable outcomes later?
LISA SU: Properly, as you mentioned, I’m most likely a techno optimist, however I’m truly a really, very pragmatic mind-set about that is the expertise will not be excellent, pretty much as good as expertise is, we’re nonetheless within the very early levels of the deployment of ai, and we do know that the ais should not all the time proper. And so a part of what we’ve got to do as a set of leaders is determine the best way to use the expertise for good and likewise shield the downsides. And look, I feel this can be a very vibrant dialog. I feel all of us are studying within the course of. I’ll say that I’ve personally discovered a ton during the last 12 plus months by way of the best way to apply AI even inside our personal firm, and likewise speaking to a lot of my friends how issues are going. And I feel we’re all acknowledge that we’re in a studying course of, however the hot button is to be very energetic in that studying. So my perception, and I do know there’s a whole lot of doomsday theories about how AI goes to take over all of our jobs. I truly am a subscriber to the assumption that what we’ve got to do as leaders of corporations is to essentially learn to harness the ability of AI and likewise deliver our workers together with that in order that we’re truly making our workers extra productive and we’re capable of make our corporations extra productive understanding that there are some areas the place we’ve got to watch out with the usage of ai.
ADI IGNATIUS: Yep, that’s useful. There’s additionally one other side of this, which is simply the stability between pace bringing merchandise out to the market as rapidly as attainable. Now that there’s a market versus warning, and that’s mirrored, as you mentioned, you’re studying and there are issues we don’t know but concerning the expertise. How do you consider—from the place you might be at AMD—how do you consider this stability between pace and warning?
LISA SU: Yeah, I actually imagine in quick experimentation and implementation. So I don’t imagine the reply is let’s decelerate. I feel what we’ve got to do is experiment. The place we’ve frolicked is we even have a Accountable AI Council. I feel all of us as leaders, for those who’re main corporations or groups, it’s important to take into consideration the best way to make the most of the expertise responsibly. We take into consideration issues about mental property, the best way to shield our mental property, in addition to defending our prospects and our companions mental property. However that being the case, I feel the ability of AI is discovering these use instances that provide you with very, very important return on funding. And we’ve seen in a few of our workflows, like in a few of our design workflows, we’ve seen what used to take weeks and months actually come all the way down to days. And when you consider how precious that’s to your enterprise, it’s important to actually push the envelope on utilizing the expertise. And there are many people who find themselves on the market to assist by way of experiences. I do know that it’s a really energetic dialog at any time when I’m speaking to my peer CEOs nowadays by way of what are you studying, the place are the use instances which might be most useful? What are the issues to watch out about? So I feel this energetic dialogue is admittedly useful,
ADI IGNATIUS: And I’d be concerned with your recommendation for individuals who, nicely, let’s say when chat GPT got here available in the market, a number of individuals experimented with it and performed round with it, and now I dunno what wave we’re on, however now it’s like, okay, however how do I truly use it? How do I truly apply it to my firm? You talked about healthcare and other people typically point out healthcare as a transparent use case, however that’s very specialised for the final viewers right here. What would your recommendation be? How do individuals determine, I assume there are two issues, the best way to shield themselves in opposition to being disrupted by AI options, however then perhaps extra pertinently, how do I exploit AI to enhance my enterprise, whether or not it’s effectivity or one thing else? What’s your recommendation for people who find themselves even simply attempting to assume via that downside?
LISA SU: Yeah, I might say once more, look throughout the use instances and the workflows in your enterprise. The locations the place it’s apparent, very, very close to time period successes may be in issues referred to as copilots or the place AI is definitely a helper to somebody, to your workers. And I take into consideration all these copilot workouts, whether or not it’s on the engineering aspect, we’re utilizing copilots to assist us design code and actually write code and to assist us take a look at take a look at instances and use instances, enhance our high quality, these sorts of issues. Once I take a look at issues which might be extra enterprise oriented, we’re how we use AI in our advertising and our communications and our content material creation. Once more, these co-pilots will assist you to, let’s name it, get near the reply. After which after all the ultimate touches are being executed by your professional workers. There are lots of, many instances like that via each enterprise the place you may take into consideration workflows, the place you may speed up your time to get a solution.
The locations the place after all it’s important to be a little bit bit extra cautious are locations that you’d rely extra on the AI itself to provide you with the reply. And there it’s important to do a whole lot of testing to just be sure you get the suitable solutions. However once more, my recommendation is a number of pilots, experimentation, after which determining the place it has probably the most worth. We’ve definitely seen as we’ve deployed AI throughout our enterprise that there are some locations the place very excessive worth, very low barrier of entry, after which there are others the place frankly the duties are it’s important to put much more work into ensuring that the fashions and the AI are extra tailored to your specific use case. So a number of experimentation and actually the place you may get probably the most bang for the buck within the close to time period.
ADI IGNATIUS: Yeah, thanks for that. So right here’s an viewers query. That is Melissa Quillan, unsure the place Melissa is, however query is, in the case of ai, how are you anticipating returning real-time information mining with the intention to pivot your enterprise virtually instantly to present developments or to resolve points that pop
LISA SU: Up? Yeah, completely. Now we have executed, there may be fairly a bit of labor and we’ve additionally executed work ourselves on issues like being extra predictive in gross sales cycles and a few of the information that comes into these developments. I might say that requires a bit of coaching on your enterprise as a result of not each enterprise is completely different and there does must be a bit of coaching in your particular information, however I do assume which you could get some very good patterns and developments that come provide you with insights of the place to dive to the subsequent stage of element going ahead.
ADI IGNATIUS: Yep. So I wish to ask you about your run at a MD. You’ve been CEO now for about 10 years. You mentioned earlier on that certainly one of your objectives was to deliver focus to the corporate. How do you establish which enterprise to prioritize and the way do you get take into consideration focus in that position?
LISA SU: Yeah, so I’ve been at a MD about 12 years, CEO for nearly 10 years. And one of many issues that’s true in each enterprise around the globe is that you’ve got extra alternatives than you’ve got individuals or sources or management bandwidth. And so for us at a MD, it was deciding actually what are we going to be greatest at? And our heritage has been certainly one of excessive efficiency computing and actually constructing on the bleeding fringe of expertise. And that was actually our focus merchandise. So there have been issues that we had to decide on to not do. For instance, cellphones are very attention-grabbing a part of semiconductors. There are many nice corporations in that space that wasn’t the proper space for a MD, and we simply needed to actually select the issues that we had been greatest at. So our focus was a excessive efficiency computing earlier than excessive efficiency computing was attractive. And now we will say between excessive efficiency computing and ai, we’re in maybe one of the vital thrilling areas, if not probably the most thrilling space in semiconductors. And it has loads to do with our heritage and focus.
ADI IGNATIUS: So I do know your purpose is to remain on the chopping fringe of expertise, the subsequent innovation. This can be a aggressive trade. And while you’re up in opposition to huge gamers like Nvidia, how do you do this?
LISA SU: Properly, the great thing about expertise, and I wish to say this very a lot, it’s about constructing nice merchandise. And to essentially do this, we truly must see the longer term. We have to determine, hey, the place’s the trade going over the subsequent three to 5 years? And we have to place huge bets on expertise. And I feel from that standpoint, it’s a type of areas that may be very rewarding for those who make the suitable huge bets. And we’ve made some excellent bets. I feel as we take a look at expertise going ahead, I’m tremendous enthusiastic about what we’re doing in ai. It’s kind of a confluence of occasions. I imply, generative AI has come into fruition and the actual fact is everyone wants AI compute expertise, and we’re one of many only a few corporations on this planet that may do this. And we’ve been actually investing on this house for the final 10 years. So it’s a type of locations the place it’s important to form of see throughout the horizon. And with that, we make investments very closely in r and d and the important thing applied sciences to allow the subsequent technology of merchandise.
ADI IGNATIUS: I like your statement. Who knew this trade can be attractive, however you’re having your second, in order that’s nice. So right here’s one other viewers query. That is Gaja and Yoga Suran, who’s asking how costly versus accessible will AI expertise be within the medium time period? And the purpose is, given the big price of supplies required for constructing semiconductors for worker headcount on the huge producers like a MD, do you see the price of accessing this expertise will restrict the flexibility of sure individuals, sure corporations to reap the benefits of what it may provide?
LISA SU: Yeah, the beauty of expertise, particularly when you consider utilization curves is we’re very cognizant of the truth that for expertise to be most broadly adopted, you do truly must get kind of the price to a really, very cheap level. So one of many issues that we’re engaged on at this time are issues like if you consider there are every kind of huge language fashions which might be utilized in ai. There’s some who’re probably the most superior, the most important, which require tens of tens of millions, a whole lot of tens of millions of {dollars}, perhaps even billions to coach. However frankly, there are methods to essentially entry extra advantageous tuned fashions that don’t require that form of funding. Or if you consider how a lot it prices to ask a query to talk GPT or certainly one of your copilots nowadays, we name that an inference alternative. We’re completely lowering the price of that by components over the subsequent couple of years. So I don’t imagine that that is going to be an total challenge the place the price is prohibitive. I feel it is a matter of it’s important to determine the place your return on funding is and the place are you going to see the most important productiveness enhancements. And that’s very a lot what we’re driving as we take a look at advancing the expertise going ahead.
ADI IGNATIUS: So your trade appears very advanced and the provision chain appears very advanced. On high of that, you’ve got the uncertainty of political and commerce points. As I mentioned, it’s a delicate trade. China lately mentioned a minimum of it was prohibiting A MD and Intel chips from authorities computer systems. How do you reply to that? Are you able to do something to attempt to transfer the needle on coverage points like this?
LISA SU: Properly, I might begin with the notion that, look, each nation has to do what they imagine is in the perfect pursuits of their nationwide pursuits. That being mentioned, the actual query that you’ve got about China’s insurance policies round authorities procured processors, that truly wasn’t new information. That was telegraphed truly late final 12 months. And so it’s one thing that, once more, we take a look at the breadth of the market that we’ve got. We’re a worldwide firm. We work in all markets. China is a big marketplace for us. And so inside that, so long as we will plan throughout the completely different markets, I don’t see it as a big issue within the enterprise. I feel the extra vital dialog is we’re very a lot about driving deep partnerships throughout the globe, and that’s with each giant corporations in addition to small corporations, startups and corporations are very regionally centered, and we’ll proceed to drive deep partnerships internationally.
ADI IGNATIUS: As I discussed at the beginning, you might be probably the most outstanding girl within the expertise trade. How do you assume the trade is doing now by way of gender fairness?
LISA SU: Properly, that’s very form of you to say that, ADI, I respect that. Look, I think about myself extraordinarily fortunate to be the place I’m. That is form of my dream job to be part of an trade that’s so vital and important to the world and be main an organization like a MD in tech. Look, there should not sufficient ladies. I imply, I feel we will say that it’s a type of areas the place we’re persistently attempting to drive extra kind of extra gender range in addition to simply total range of thought. And the rationale for that’s, frankly, is we wish to construct the perfect enterprise and we wish to construct the perfect merchandise. And to try this, you do want range of experiences and ideas. I’m an enormous believer in the perfect factor that we will do is give individuals alternatives. I used to be very fortunate in my profession and I bought an opportunity to essentially expertise many issues early on in my profession, which helped give me some nice experiences. And in order that’s very a lot what I’m centered on doing is giving ladies kind of extra publicity to the trade total after which alternatives to shine and kind of show their capabilities going ahead.
ADI IGNATIUS: So there’s additionally the query of I assume, age range. David Dawson, a viewer requested, do you see any clear alternatives or gaps the place new views? And I feel by that he means new graduates, younger staff will likely be useful, and let’s say significantly in ai.
LISA SU: Yeah, look, we’re all the time on the lookout for new expertise. I imply, we’ve considerably grown as an organization. Once I first began as CEO, we had been about 8,000 individuals. We’re now about north of 25,000. So a number of development during the last 10 years. And I feel the important thing for that may be a range of perspective is tremendous vital. And what I wish to say, particularly after we’re on the lookout for new graduates, we don’t view hiring any individual at a faculty as job coaching. We’re not on the lookout for that actual software program talent to plug right into a software program workforce. What we’re on the lookout for is people who find themselves nice thinkers, who’re nice downside solvers, who’re right here to construct a profession and right here to be taught a whole lot of various things. And alongside the way in which, we’re going to wish your {hardware} expertise and your software program expertise and your downside fixing expertise. And so sure, I feel range of thought is admittedly vital. We love new graduates out of college and we rent internationally that new hires yearly, and we’ll proceed to diversify our expertise base going ahead.
ADI IGNATIUS: So you may’t do an HBR interview with out getting a minimum of one basic HBR query. So right here’s my basic HBR query. In your decade as CEO, what’s a very powerful lesson that you just’ve discovered in these 10 years?
LISA SU: Yeah, so I feel a very powerful lesson that I’ve discovered is to essentially be very bold within the long-term objectives that you just set for an organization. I imply, if you consider the place we had been, we had been a 4 billion firm in 2015, and we’re now north of twenty-two, 20 3 billion final 12 months. I feel setting very bold objectives for the workforce whereas having very clear milestones for a way we present progress alongside the way in which. Definitely in our enterprise it’s about long-term considering and charting a method for that, however everybody wants some close to time period milestones as nicely.
ADI IGNATIUS: So there’s an viewers query that has gotten a number of up votes you can do with it no matter you need. That is from Bahar Dunno the place Bahar is from. However Bihar’s query is, what are you studying now?
LISA SU: Oh, wow. That’s an awesome query. I learn a whole lot of issues on-line truly. And imagine it or not, I’m a fairly avid consumer of each Reddit and X as a result of they really helped me get excellent real-time info of what’s occurring on this planet.
ADI IGNATIUS: Okay. And final query. So a few individuals have requested, are you utilizing on the subject of sustainability, is AI serving to AMD obtain its objectives for sustainability? After which extra broadly, do you see AI taking part in a task in influencing sustainability or CSR efforts for you or for others?
LISA SU: Yeah, let me flip it across the different method. I imply, our expertise is definitely very centered on sustainability. So the thought of the place expertise goes, give it some thought as not nearly excessive efficiency, nevertheless it’s about what efficiency are you able to get at a sure PowerPoint. So we’re all about, when you consider at this time’s limitations, frankly energy will likely be a limitation as you go ahead. And so we’re continually how can we be extra environment friendly with our merchandise, which assist the general sustainability dialog. Now because it pertains to ai, I do completely imagine that AI will assist us in sustainability from the standpoint of it can get us to solutions extra effectively. And with that you just want much less energy for that, that being the case. There’s additionally the reverse pattern, which is we’re utilizing much more computing to assist us modernize our companies. So a whole lot of concentrate on sustainability. What I might undoubtedly say to this viewers is that the newer the expertise, frankly, the extra sustainable it’s since you do have the entire advantages of newer applied sciences being a lot, way more energy environment friendly. So that you want a lot much less energy to get the job executed.
ADI IGNATIUS: So Lisa, I wish to thanks for being at this occasion. I’ve lengthy admired you and lengthy admired A MD, so it’s very nice to have this dialog. So thanks for being right here.
LISA SU: Thanks a lot for having me this morning.
HANNAH BATES: That was AMD CEO Lisa Su in dialog with HBR Editor at Massive Adi Ignatius.
We’ll be again subsequent Wednesday with one other hand-picked dialog about enterprise technique from the Harvard Enterprise Overview. Should you discovered this episode useful, share it with your pals and colleagues, and observe our present on Apple Podcasts, Spotify, or wherever you get your podcasts. When you’re there, remember to go away us a assessment.
And while you’re prepared for extra podcasts, articles, case research, books, and movies with the world’s high enterprise and administration specialists, discover all of it at HBR.org.
This episode was produced by Dave DiIulio, Elie Honein, Terry Cole, Julia Butler, and me—Hannah Bates. Curt Nickisch is our editor. Particular because of Ian Fox, Maureen Hoch, Erica Truxler, Ramsey Khabbaz, Nicole Smith, Anne Bartholomew, and also you – our listener. See you subsequent week.
You might also like
HANNAH BATES: Welcome to HBR On Technique—case research and conversations with the world’s high enterprise and administration specialists, hand-selected that will help you unlock new methods of doing enterprise.
As CEO, Lisa Su has remodeled AMD into one of many quickest rising semiconductor companies on this planet. She has additionally seen firsthand the way in which AI is reshaping corporations and whole industries. On this dialog with Adi Ignatius throughout HBR’s 2024 Leaders Who Make a Distinction convention, she explains how leaders can responsibly harness AI to spice up their productiveness—and keep aggressive. Her largest piece of recommendation? Experiment aggressively. Su shares what that’s seemed like at AMD, and the way your organization can undertake the same technique.
ADI IGNATIUS: So each dialog about AI that I’ve finally evolves into one thing very darkish that’s ai an existentialist menace in a roundabout way to not simply our jobs, however to our very existence. I’m assuming you’re a relative techno optimist, however assist us out if AI goes to be a pressure for good, how does that occur? Will it occur? Will expertise save us from the draw back of expertise, or will we, all of us must be contributing to the dialogue now to verify we don’t get the worst attainable outcomes later?
LISA SU: Properly, as you mentioned, I’m most likely a techno optimist, however I’m truly a really, very pragmatic mind-set about that is the expertise will not be excellent, pretty much as good as expertise is, we’re nonetheless within the very early levels of the deployment of ai, and we do know that the ais should not all the time proper. And so a part of what we’ve got to do as a set of leaders is determine the best way to use the expertise for good and likewise shield the downsides. And look, I feel this can be a very vibrant dialog. I feel all of us are studying within the course of. I’ll say that I’ve personally discovered a ton during the last 12 plus months by way of the best way to apply AI even inside our personal firm, and likewise speaking to a lot of my friends how issues are going. And I feel we’re all acknowledge that we’re in a studying course of, however the hot button is to be very energetic in that studying. So my perception, and I do know there’s a whole lot of doomsday theories about how AI goes to take over all of our jobs. I truly am a subscriber to the assumption that what we’ve got to do as leaders of corporations is to essentially learn to harness the ability of AI and likewise deliver our workers together with that in order that we’re truly making our workers extra productive and we’re capable of make our corporations extra productive understanding that there are some areas the place we’ve got to watch out with the usage of ai.
ADI IGNATIUS: Yep, that’s useful. There’s additionally one other side of this, which is simply the stability between pace bringing merchandise out to the market as rapidly as attainable. Now that there’s a market versus warning, and that’s mirrored, as you mentioned, you’re studying and there are issues we don’t know but concerning the expertise. How do you consider—from the place you might be at AMD—how do you consider this stability between pace and warning?
LISA SU: Yeah, I actually imagine in quick experimentation and implementation. So I don’t imagine the reply is let’s decelerate. I feel what we’ve got to do is experiment. The place we’ve frolicked is we even have a Accountable AI Council. I feel all of us as leaders, for those who’re main corporations or groups, it’s important to take into consideration the best way to make the most of the expertise responsibly. We take into consideration issues about mental property, the best way to shield our mental property, in addition to defending our prospects and our companions mental property. However that being the case, I feel the ability of AI is discovering these use instances that provide you with very, very important return on funding. And we’ve seen in a few of our workflows, like in a few of our design workflows, we’ve seen what used to take weeks and months actually come all the way down to days. And when you consider how precious that’s to your enterprise, it’s important to actually push the envelope on utilizing the expertise. And there are many people who find themselves on the market to assist by way of experiences. I do know that it’s a really energetic dialog at any time when I’m speaking to my peer CEOs nowadays by way of what are you studying, the place are the use instances which might be most useful? What are the issues to watch out about? So I feel this energetic dialogue is admittedly useful,
ADI IGNATIUS: And I’d be concerned with your recommendation for individuals who, nicely, let’s say when chat GPT got here available in the market, a number of individuals experimented with it and performed round with it, and now I dunno what wave we’re on, however now it’s like, okay, however how do I truly use it? How do I truly apply it to my firm? You talked about healthcare and other people typically point out healthcare as a transparent use case, however that’s very specialised for the final viewers right here. What would your recommendation be? How do individuals determine, I assume there are two issues, the best way to shield themselves in opposition to being disrupted by AI options, however then perhaps extra pertinently, how do I exploit AI to enhance my enterprise, whether or not it’s effectivity or one thing else? What’s your recommendation for people who find themselves even simply attempting to assume via that downside?
LISA SU: Yeah, I might say once more, look throughout the use instances and the workflows in your enterprise. The locations the place it’s apparent, very, very close to time period successes may be in issues referred to as copilots or the place AI is definitely a helper to somebody, to your workers. And I take into consideration all these copilot workouts, whether or not it’s on the engineering aspect, we’re utilizing copilots to assist us design code and actually write code and to assist us take a look at take a look at instances and use instances, enhance our high quality, these sorts of issues. Once I take a look at issues which might be extra enterprise oriented, we’re how we use AI in our advertising and our communications and our content material creation. Once more, these co-pilots will assist you to, let’s name it, get near the reply. After which after all the ultimate touches are being executed by your professional workers. There are lots of, many instances like that via each enterprise the place you may take into consideration workflows, the place you may speed up your time to get a solution.
The locations the place after all it’s important to be a little bit bit extra cautious are locations that you’d rely extra on the AI itself to provide you with the reply. And there it’s important to do a whole lot of testing to just be sure you get the suitable solutions. However once more, my recommendation is a number of pilots, experimentation, after which determining the place it has probably the most worth. We’ve definitely seen as we’ve deployed AI throughout our enterprise that there are some locations the place very excessive worth, very low barrier of entry, after which there are others the place frankly the duties are it’s important to put much more work into ensuring that the fashions and the AI are extra tailored to your specific use case. So a number of experimentation and actually the place you may get probably the most bang for the buck within the close to time period.
ADI IGNATIUS: Yeah, thanks for that. So right here’s an viewers query. That is Melissa Quillan, unsure the place Melissa is, however query is, in the case of ai, how are you anticipating returning real-time information mining with the intention to pivot your enterprise virtually instantly to present developments or to resolve points that pop
LISA SU: Up? Yeah, completely. Now we have executed, there may be fairly a bit of labor and we’ve additionally executed work ourselves on issues like being extra predictive in gross sales cycles and a few of the information that comes into these developments. I might say that requires a bit of coaching on your enterprise as a result of not each enterprise is completely different and there does must be a bit of coaching in your particular information, however I do assume which you could get some very good patterns and developments that come provide you with insights of the place to dive to the subsequent stage of element going ahead.
ADI IGNATIUS: Yep. So I wish to ask you about your run at a MD. You’ve been CEO now for about 10 years. You mentioned earlier on that certainly one of your objectives was to deliver focus to the corporate. How do you establish which enterprise to prioritize and the way do you get take into consideration focus in that position?
LISA SU: Yeah, so I’ve been at a MD about 12 years, CEO for nearly 10 years. And one of many issues that’s true in each enterprise around the globe is that you’ve got extra alternatives than you’ve got individuals or sources or management bandwidth. And so for us at a MD, it was deciding actually what are we going to be greatest at? And our heritage has been certainly one of excessive efficiency computing and actually constructing on the bleeding fringe of expertise. And that was actually our focus merchandise. So there have been issues that we had to decide on to not do. For instance, cellphones are very attention-grabbing a part of semiconductors. There are many nice corporations in that space that wasn’t the proper space for a MD, and we simply needed to actually select the issues that we had been greatest at. So our focus was a excessive efficiency computing earlier than excessive efficiency computing was attractive. And now we will say between excessive efficiency computing and ai, we’re in maybe one of the vital thrilling areas, if not probably the most thrilling space in semiconductors. And it has loads to do with our heritage and focus.
ADI IGNATIUS: So I do know your purpose is to remain on the chopping fringe of expertise, the subsequent innovation. This can be a aggressive trade. And while you’re up in opposition to huge gamers like Nvidia, how do you do this?
LISA SU: Properly, the great thing about expertise, and I wish to say this very a lot, it’s about constructing nice merchandise. And to essentially do this, we truly must see the longer term. We have to determine, hey, the place’s the trade going over the subsequent three to 5 years? And we have to place huge bets on expertise. And I feel from that standpoint, it’s a type of areas that may be very rewarding for those who make the suitable huge bets. And we’ve made some excellent bets. I feel as we take a look at expertise going ahead, I’m tremendous enthusiastic about what we’re doing in ai. It’s kind of a confluence of occasions. I imply, generative AI has come into fruition and the actual fact is everyone wants AI compute expertise, and we’re one of many only a few corporations on this planet that may do this. And we’ve been actually investing on this house for the final 10 years. So it’s a type of locations the place it’s important to form of see throughout the horizon. And with that, we make investments very closely in r and d and the important thing applied sciences to allow the subsequent technology of merchandise.
ADI IGNATIUS: I like your statement. Who knew this trade can be attractive, however you’re having your second, in order that’s nice. So right here’s one other viewers query. That is Gaja and Yoga Suran, who’s asking how costly versus accessible will AI expertise be within the medium time period? And the purpose is, given the big price of supplies required for constructing semiconductors for worker headcount on the huge producers like a MD, do you see the price of accessing this expertise will restrict the flexibility of sure individuals, sure corporations to reap the benefits of what it may provide?
LISA SU: Yeah, the beauty of expertise, particularly when you consider utilization curves is we’re very cognizant of the truth that for expertise to be most broadly adopted, you do truly must get kind of the price to a really, very cheap level. So one of many issues that we’re engaged on at this time are issues like if you consider there are every kind of huge language fashions which might be utilized in ai. There’s some who’re probably the most superior, the most important, which require tens of tens of millions, a whole lot of tens of millions of {dollars}, perhaps even billions to coach. However frankly, there are methods to essentially entry extra advantageous tuned fashions that don’t require that form of funding. Or if you consider how a lot it prices to ask a query to talk GPT or certainly one of your copilots nowadays, we name that an inference alternative. We’re completely lowering the price of that by components over the subsequent couple of years. So I don’t imagine that that is going to be an total challenge the place the price is prohibitive. I feel it is a matter of it’s important to determine the place your return on funding is and the place are you going to see the most important productiveness enhancements. And that’s very a lot what we’re driving as we take a look at advancing the expertise going ahead.
ADI IGNATIUS: So your trade appears very advanced and the provision chain appears very advanced. On high of that, you’ve got the uncertainty of political and commerce points. As I mentioned, it’s a delicate trade. China lately mentioned a minimum of it was prohibiting A MD and Intel chips from authorities computer systems. How do you reply to that? Are you able to do something to attempt to transfer the needle on coverage points like this?
LISA SU: Properly, I might begin with the notion that, look, each nation has to do what they imagine is in the perfect pursuits of their nationwide pursuits. That being mentioned, the actual query that you’ve got about China’s insurance policies round authorities procured processors, that truly wasn’t new information. That was telegraphed truly late final 12 months. And so it’s one thing that, once more, we take a look at the breadth of the market that we’ve got. We’re a worldwide firm. We work in all markets. China is a big marketplace for us. And so inside that, so long as we will plan throughout the completely different markets, I don’t see it as a big issue within the enterprise. I feel the extra vital dialog is we’re very a lot about driving deep partnerships throughout the globe, and that’s with each giant corporations in addition to small corporations, startups and corporations are very regionally centered, and we’ll proceed to drive deep partnerships internationally.
ADI IGNATIUS: As I discussed at the beginning, you might be probably the most outstanding girl within the expertise trade. How do you assume the trade is doing now by way of gender fairness?
LISA SU: Properly, that’s very form of you to say that, ADI, I respect that. Look, I think about myself extraordinarily fortunate to be the place I’m. That is form of my dream job to be part of an trade that’s so vital and important to the world and be main an organization like a MD in tech. Look, there should not sufficient ladies. I imply, I feel we will say that it’s a type of areas the place we’re persistently attempting to drive extra kind of extra gender range in addition to simply total range of thought. And the rationale for that’s, frankly, is we wish to construct the perfect enterprise and we wish to construct the perfect merchandise. And to try this, you do want range of experiences and ideas. I’m an enormous believer in the perfect factor that we will do is give individuals alternatives. I used to be very fortunate in my profession and I bought an opportunity to essentially expertise many issues early on in my profession, which helped give me some nice experiences. And in order that’s very a lot what I’m centered on doing is giving ladies kind of extra publicity to the trade total after which alternatives to shine and kind of show their capabilities going ahead.
ADI IGNATIUS: So there’s additionally the query of I assume, age range. David Dawson, a viewer requested, do you see any clear alternatives or gaps the place new views? And I feel by that he means new graduates, younger staff will likely be useful, and let’s say significantly in ai.
LISA SU: Yeah, look, we’re all the time on the lookout for new expertise. I imply, we’ve considerably grown as an organization. Once I first began as CEO, we had been about 8,000 individuals. We’re now about north of 25,000. So a number of development during the last 10 years. And I feel the important thing for that may be a range of perspective is tremendous vital. And what I wish to say, particularly after we’re on the lookout for new graduates, we don’t view hiring any individual at a faculty as job coaching. We’re not on the lookout for that actual software program talent to plug right into a software program workforce. What we’re on the lookout for is people who find themselves nice thinkers, who’re nice downside solvers, who’re right here to construct a profession and right here to be taught a whole lot of various things. And alongside the way in which, we’re going to wish your {hardware} expertise and your software program expertise and your downside fixing expertise. And so sure, I feel range of thought is admittedly vital. We love new graduates out of college and we rent internationally that new hires yearly, and we’ll proceed to diversify our expertise base going ahead.
ADI IGNATIUS: So you may’t do an HBR interview with out getting a minimum of one basic HBR query. So right here’s my basic HBR query. In your decade as CEO, what’s a very powerful lesson that you just’ve discovered in these 10 years?
LISA SU: Yeah, so I feel a very powerful lesson that I’ve discovered is to essentially be very bold within the long-term objectives that you just set for an organization. I imply, if you consider the place we had been, we had been a 4 billion firm in 2015, and we’re now north of twenty-two, 20 3 billion final 12 months. I feel setting very bold objectives for the workforce whereas having very clear milestones for a way we present progress alongside the way in which. Definitely in our enterprise it’s about long-term considering and charting a method for that, however everybody wants some close to time period milestones as nicely.
ADI IGNATIUS: So there’s an viewers query that has gotten a number of up votes you can do with it no matter you need. That is from Bahar Dunno the place Bahar is from. However Bihar’s query is, what are you studying now?
LISA SU: Oh, wow. That’s an awesome query. I learn a whole lot of issues on-line truly. And imagine it or not, I’m a fairly avid consumer of each Reddit and X as a result of they really helped me get excellent real-time info of what’s occurring on this planet.
ADI IGNATIUS: Okay. And final query. So a few individuals have requested, are you utilizing on the subject of sustainability, is AI serving to AMD obtain its objectives for sustainability? After which extra broadly, do you see AI taking part in a task in influencing sustainability or CSR efforts for you or for others?
LISA SU: Yeah, let me flip it across the different method. I imply, our expertise is definitely very centered on sustainability. So the thought of the place expertise goes, give it some thought as not nearly excessive efficiency, nevertheless it’s about what efficiency are you able to get at a sure PowerPoint. So we’re all about, when you consider at this time’s limitations, frankly energy will likely be a limitation as you go ahead. And so we’re continually how can we be extra environment friendly with our merchandise, which assist the general sustainability dialog. Now because it pertains to ai, I do completely imagine that AI will assist us in sustainability from the standpoint of it can get us to solutions extra effectively. And with that you just want much less energy for that, that being the case. There’s additionally the reverse pattern, which is we’re utilizing much more computing to assist us modernize our companies. So a whole lot of concentrate on sustainability. What I might undoubtedly say to this viewers is that the newer the expertise, frankly, the extra sustainable it’s since you do have the entire advantages of newer applied sciences being a lot, way more energy environment friendly. So that you want a lot much less energy to get the job executed.
ADI IGNATIUS: So Lisa, I wish to thanks for being at this occasion. I’ve lengthy admired you and lengthy admired A MD, so it’s very nice to have this dialog. So thanks for being right here.
LISA SU: Thanks a lot for having me this morning.
HANNAH BATES: That was AMD CEO Lisa Su in dialog with HBR Editor at Massive Adi Ignatius.
We’ll be again subsequent Wednesday with one other hand-picked dialog about enterprise technique from the Harvard Enterprise Overview. Should you discovered this episode useful, share it with your pals and colleagues, and observe our present on Apple Podcasts, Spotify, or wherever you get your podcasts. When you’re there, remember to go away us a assessment.
And while you’re prepared for extra podcasts, articles, case research, books, and movies with the world’s high enterprise and administration specialists, discover all of it at HBR.org.
This episode was produced by Dave DiIulio, Elie Honein, Terry Cole, Julia Butler, and me—Hannah Bates. Curt Nickisch is our editor. Particular because of Ian Fox, Maureen Hoch, Erica Truxler, Ramsey Khabbaz, Nicole Smith, Anne Bartholomew, and also you – our listener. See you subsequent week.
