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- [00:00]
Arvind Krishna
Get out of the headlines and into real conversations happening inside global organizations with the Executive Insights Podcast brought to you by aws.
- [00:09]
Kelly Cavagnaro
Listen in on the Executive Insights Podcast.
- [00:12]
Arvind Krishna
Available on all major podcast platforms.
- [00:19]
Kelly Cavagnaro
Hey, what's news, listeners? It's Sunday, September 21st. I'm Alex Osola for the Wall Street Journal. This is what's New Sunday, the show where we tackle the big questions about the biggest stories in the news by reaching out to our colleagues across the newsroom. Help explain what's happening in our world. This week, we're bringing you an episode of WSJ's Bold Names, where co hosts Christopher Mims and Tim Higgins speak to CEOs and business leaders, taking you inside the decisions being made in the C Suite and beyond. In this episode, they're joined by IBM CEO Arvind Krishna. After spending much of the 2010s in the doldrums, IBM has made something of a comeback in recent years, largely due to the success of its hybrid cloud business and consulting services. Now the company is placing a big bet on quantum computing, which it hopes to be commercially viable in the next five years. Tim and Christopher talked to Krishna about how IBM plans to compete against rivals in the quantum space and how to ensure that it doesn't get there too early.
- [01:21]
Christopher Mims
America used to run on IBM. It was the backbone of business. The solution is IBM, but after getting that jingle stuck in the heads of millions of Americans in the late 1980s, Big Blue lost its swagger.
- [01:36]
Arvind Krishna
IBM is getting a lot of attention today. More now on that big miss for IBM, on both earnings and revenue. It's been a rough go, there's no doubt about it, you know, in terms of trying.
- [01:46]
Tim Higgins
IBM spent much of the 2010s in the doldrums, but has made something of a comeback in the past five years. That's thanks to a lot of the success in its hybrid cloud business. They've also leaned heavily into consulting services, all of which has led to a surge in the company's share price. That's under the leadership of CEO Arvind Krishna. He took the reins in 2020, and.
- [02:10]
Christopher Mims
Now IBM's looking to the future with quantum computing, something I saw firsthand earlier this summer. I'm standing outside the Thomas J. Watson IBM Research center in Yorktown Heights, New York. Believe it or not, this is probably the leading lab in the world for quantum quantum computing research. We're going to go inside today and see what all of that is.
- [02:33]
Tim Higgins
Regular computers are essentially binary. They make computations using on and off switches. The different arrangements of These switches are called bits. But quantum computers use a different kind of bit, what's known in the business as a qubit. This opens up a huge range of new computational possibilities. It's going to get technical at times, but hang on, because it's going to be worth it. You'll hear Arvind talk about something called carbon sequestration, for example, or capturing carbon from the atmosphere and storing it to help lower greenhouse gas emissions. A quantum computer can help with that.
- [03:14]
Christopher Mims
But betting on the next big thing hasn't always worked out for IBM. Just look at AI. In 2011, IBM's Watson AI famously beat Ken Jennings on Jeopardy.
- [03:25]
Tim Higgins
Usually when I play Jeopardy. It's just for the fun of it.
- [03:27]
Arvind Krishna
And this time I feel like it's.
- [03:28]
Tim Higgins
All part of some vast socio technological experiment. What is Jericho?
- [03:32]
Arvind Krishna
Correct.
- [03:34]
Christopher Mims
It was kind of downhill from there. It felt like IBM had lost the plot. Now we ask Arvind Krishna how IBM is going to recapture the future through quantum computing.
- [03:49]
Tim Higgins
From the Wall Street Journal, I'm Tim Higgins.
- [03:51]
Christopher Mims
And I'm Christopher Mims. This is Bold Names, where you'll hear from the leaders of the bold name companies featured in the pages of the Wall Street Journal.
- [04:00]
Arvind Krishna
Today.
- [04:00]
Tim Higgins
We ask, why does Big Blue think it can crack quantum?
- [04:09]
Christopher Mims
Arvind, welcome. I'm excited to have you here in part because I was just at your Thomas J. Watson Research center in Yorktown Heights. Very impressive. Built in the 60s, looks like the set of a Kubrick film. And I got to spend time with your head of quantum hardware, Jerry Chow. The technology here is really complicated. I spent three hours with Jerry, and basically my summary of how your quantum computing works is that it's magic. So I want to skip over the hour we could spend describing how this works and go straight to applications. What applications of your quantum computing technology are you the most excited about?
- [04:54]
Arvind Krishna
I think the reason we are so excited about quantum is its ability to solve problems that normal computers cannot. And actually, I'll make a stronger statement, will not solve. So if we want to understand how materials really work, as an example, could we design a molecule that's better for carbon sequestration? Could we come up with a way to fix nitrogen so that we can increase food production and quality in the world? Because that's fertilizers. To make it simple, could we come up with a coating to reduce corrosion in underwater pipes so oil and gas don't ever leak into the ocean? Those are the kinds of problems that I'm super excited about.
- [05:37]
Christopher Mims
Right, because you're talking about doing simulations of quantum effects. And funny enough, you need a quantum computer to simulate the way atoms behave at that level.
- [05:49]
Arvind Krishna
Richard Feynman's quote, if you want to simulate nature, you need a quantum computer. He added some more colorful language, but for the podcast, I'll stop there. And to give a bit of intuition, when you begin to look at these materials or even simple molecules, you very quickly get into this 30, 40, 100 electrons. And in order to compute them, that's impossible. If you try to simulate them on a normal computer, you begin to need the amount of memory exceeds that that is even possible because 2 to the 200 is a number we just can't fathom in terms of the amount of state that is needed. Quantum computers will be able to do that shortly.
- [06:35]
Tim Higgins
So a bunch of other tech companies are also eyeing quantum. Right, You've got Google, you've got Microsoft, which have reported some pretty exciting breakthroughs in the past year. So why is IBM the company that's finally going to crack this technology?
- [06:52]
Arvind Krishna
So I'm going to give you a couple of statements which are somewhat dissonant. Number one, I love the fact really, I really love the fact that a few dozen or more others are going after this technology, why it helps to make a market. Because if it's just us, you'll begin to question, why should I believe you? Well, if others aren't trying it, is it really of any value? So actually incredibly useful from a client government as well as I'll say from a media perspective that there's many others, because I think that defines a market as opposed to not the race for the future right now it comes to. So why would we be a winner of the race? And you know, Tim, I'm saying a winner, not the only winner. I got it. I want my technology teams to be super excited to be the only winner. But as long as we are a winner, I'm good. Okay, so now why would we do that? I think a lot of people are working on incredibly exciting and we haven't yet used the term qubit, but let's think of that as a fundamental building block of a quantum computer. Not the only, but a fundamental building block. Lots of people are working on really exciting qubit technologies. I think that's great because it opens up many options and science usually advances by people standing on each other's shoulders. So actually I think that's wonderful. But now you need to connect thousands of qubits together because to compute you need to have, let's call it signals flow from one to the other. Then it's not enough to have those connected. You need to be able to read and write to it. Then you need to be able to have it function all day, all week and all month without needing a team of PhDs to come and tune it between every single run. Because if that's the case, that's not really a computer.
- [08:53]
Christopher Mims
And that's really the game, though, ultimately. Reliability.
- [08:57]
Arvind Krishna
A couple of different answers to what you're describing. Number one, we need the computer to function. Then there is the whole question of. Because you're trying to operate in very, very tiny energy states. That's the point of the cooling. Cool it down so that the normal thermal effects can be taken out of the picture because they're not going to happen at the super cold temperatures. Christopher, to be candid, that's a pretty straightforward problem. Yeah, it sounds interesting.
- [09:29]
Christopher Mims
No big deal, just colder than deep space.
- [09:32]
Arvind Krishna
It sounds like one of those, you know, really, you said Kubrick. I'll say Arthur C. Clark. Same difference there. I read you because I'm thinking in channeling 2001 A Space Odyssey. Open the pod bay doors, Hall. I'm sorry, Dave. I'm afraid I can't do that. And it begins to sound like some kind of industrial or maybe post apocalyptic scenario. But that is actually pretty standard technology to me. It's arcane. It's not ultra cheap, but neither is it ultra expensive. So let's put aside the cooling and all of the things. The question becomes, can you take what is inherently going to be unreliable? I make that very strong statement at a single qubit level and stitch it together using, I'll use the word coding techniques so that what is there is a lot more resilient to errors. All that said, it's still going to be resilient to errors for maybe 100 milliseconds to a second and then you have to start again. So how much competition can you get done in that amount of time is, I think, the singular measurement for quantum computers.
- [10:53]
Tim Higgins
Well, so a lot of math there, a lot of science, a lot of science fiction references. We got a lot there. How we're more maybe. When do you realistically expect to see a return on IBM's massive investment in this area? When do you expect this to be commercial? When do you expect this to start happening?
- [11:14]
Arvind Krishna
I would tell you that we are looking at 2029, 2030. So that is four to five years out for that return that you're talking about now. That's the beginning of the return. And then you'll begin to See people beginning to use these. Then I think the year or two after there'll be even more. And then a year or two after there'll be even more. We have seen what happens when technology begins to work into scale. The first few years are remarkably exciting about adoption.
- [11:46]
Christopher Mims
Coming up. IBM has built up billions in generative AI contracts, mostly for consulting. But as AI continues to change work, how could it disrupt that business?
- [11:59]
Arvind Krishna
Do I fully believe that work will be replaced by AI and the collection, reasoning, AI agents, all of that. I'm actually firmly convinced of that. We are running hard towards making that happen.
- [12:14]
Christopher Mims
Stay with us.
- [12:17]
Tim Higgins
At kpmg, we make the difference by creating value like developing strategic insights that help drive M and a success or embedding AI solutions into your business to sustain competitive advantage. KPMG make the difference. Learn more at www.kpmg.us insights.
- [12:41]
Christopher Mims
For anybody listening, in case they haven't guessed, you are an engineer. You are the first engineer at heart ever. How is that helping you navigate this time? Because this is a time of, I would say this is a time of more rapid change for IBM than at any point in the entire history of me watching your company.
- [13:02]
Arvind Krishna
I kind of call it. I'm an unabashed technologist and geek at heart. I love trying to figure out and hear explanations of how these things work because that, I think Christopher, answers the question you're asking. So how does it help me when you have these really intrinsic and arcane technologies that kind of seem like science fiction, having a bit of the background, it helps me understand kind of two things. One, it is going to take time, so we are still four years out. But two, when we get there, I now know how to scale really, really quickly to go get it into lots of people's hands. So it helps make those decisions and it also makes the conversation much, much faster by the teams that work on it. Because I don't have to go through a layer of, I'll call it intermediaries or trying to translate it into a different language. I mean, they can talk to me how they want to. I may understand maybe half of it, but that's better than understanding only 1% of it.
- [14:07]
Christopher Mims
And I just want to flag what you've already mentioned, which is that 2029 is when you're going to really start scaling your quantum computing efforts with Starling, right?
- [14:16]
Arvind Krishna
Correct, Christopher. But for the following reasons. We got two steps to do between now and then. Number one, you got to get these systems much bigger. Number two, you've got to prove that the Error correction works.
- [14:31]
Christopher Mims
Clearly you've got a lot of momentum. You were early to Quantum, you're kind of the belle of the ball. But how do you stay ahead? How do you maintain this momentum?
- [14:39]
Arvind Krishna
Look, Quantum is pretty straightforward. To maintain the momentum, we have to grow a very large ecosystem on Quantum. So the use cases multiply and we might perhaps collect 10% of the value. 90% of the value should go to the people and the consumers of the technology, not to us. So educating people, teaching them how to use quantum, unlocking their imagination is a big part of what we have to do. And I'm honest about the 1090 trade off. I think that that is where it has to go. Otherwise the technology doesn't really scale in the, in the.
- [15:15]
Tim Higgins
Today though, I think investors are very excited about the potential for AI and where they see IBM playing in that space. That's the hot technology of the moment in the Valley. And in a lot of investors mind, since you became CEO in early 2020, this IBM stock has just been on a tear, right? I think your stock in a lot of way is trading with the kind of premium that you see with the AI heavyweights out there. And I wonder, I want to talk a little bit about how you kind of see AI in the business and how you're balancing kind of that with your traditional role. Because I think one of the things that IBM has received a lot of praise for under your tenure is really clarifying its consulting business, right? You've worked to make IBM really a facilitator for your clients, making this tech transformation, not necessarily steering them into IBM products per se, but growing a consulting business. And I wonder, with AI, doesn't AI potentially disrupt your consulting business as it changes work in general? Do you go to bed afraid at night or excited at night?
- [16:24]
Arvind Krishna
Yeah, I am actually excited. I lose no sleep over what AI will do to our consulting teams. Why do I say that? Do I fully believe that? And we can debate, is it a third, is it half? Is it 2/3 of what people do in consulting? That work will be replaced by AI and the collection, reasoning, agents, all of that. I'm actually firmly convinced of that. We are running hard towards making that happen. So you then say, wait, if half the work happens, don't you lose half your consulting business? And I go to, no, the exact opposite happens. If we run towards it, that means we are more productive in giving people consulting help. If you are more productive, history has shown that the more productive company gains market share because if you offer higher quality things at a lower unit cost. You tend to take market share. And if you take market share, you'll actually win more customers. So that is why I believe that that is the route we need to go and go at it hard. And that is how we are going to go win.
- [17:35]
Tim Higgins
For AI and for big company adoption, or just company adoption in general, it seems like we're still in this area, this era, mostly experimental, trying to figure out how this might be useful. We're seeing some early, early things. But I'm curious what you're hearing from customers and how that conversation is changing on what they want from AI in the now and the next few years in the tangible.
- [18:02]
Arvind Krishna
So let's acknowledge the vast majority, as in, over 80% of the clients we talk to will acknowledge they're still in the era of AI experimentation. Typical conversation goes like, how many AI PoCs are you doing? I'm using proof of concepts as the jargon for experiments. Oh, I'm doing 100. I'm so proud of it. I got every function doing a little bit. Okay, how many of them do you think are going to scale? And they kind of look at their shoes, like one of them told me. Well, I think maybe three. I said like, so is the flaw in your design of how you're using AI, and then they begin to acknowledge, and that is the push now on the ROI point. ROI is only achieved when a technology begins to give value back to the business. Doing the experiment has no value in itself except to prove feasibility. So they've all begun to ask the question now, how do I scale and how do I get that value? That means I need common tool sets across the different experiments. I need to think about some of the questions up front, like, what is the lifecycle of a model? What is the governance? How do I make sure that I am correct about privacy and all the other aspects that we always need when we are dealing with data and with critical functions. And so if I was to use a sports analogy, I will tell you, AI is in the first innings. So players are on the field, you know who's going to play. But it's still early, early to see how the game works out and how it goes along.
- [19:41]
Tim Higgins
After the break, how is IBM reinventing itself for a new era?
- [19:47]
Arvind Krishna
If you're overly wedded to your past and you find it really hard to let go, then effectively you're forcing your engineers and your sales teams to be very, very defensive in front of clients. And that is not usually a good practice.
- [20:05]
Tim Higgins
That's, you know, listening to you talk about Quantum, I mean, clearly you're excited about it, Right? But I also feel like you're tempering your enthusiasm a little bit. The old IBM perhaps, and I think of kind of the AI IBM talking about Watson.
- [20:33]
Arvind Krishna
Watson, who is Agatha Christie.
- [20:36]
Tim Higgins
The appearance on Jeopardy. There was all those ads. Yet Watson, I think ultimately was a little bit disappointing to a lot of folks. It was maybe ahead of its time. And this time around with Quantum, it feels like you're trying to walk a line between being excited and enthusiastic, but also not over promising. And I wonder what that is like for you, especially in an era where nobody is tempering any enthusiasm, especially when it comes to the next technology. Right. I mean, we're seeing sky high valuations and huge amounts of money pouring into technology on the hope, on the hope that it'll happen.
- [21:13]
Arvind Krishna
Look, I think maybe being a technologist and understanding these things helps a little bit here when you're still three to four years away. And I'm acknowledging that on Quantum, why would I want to hype it up today? Because that means some client might misread it and come to me and say, hey, can I use it tomorrow? And that's not there. I really want to take an approach. Look, we're not afraid of marketing and sales. I think IBM is reasonably well known for being willing to do that. But I want to do it through the lens of my client and the lens of the people who use it. When I have that lens and they're talking about the value they derive from it, you'll find us not at all shy or abashed about going there. But right now it will be us describing what's possible, not the end user describing how excited they are about what they could do with it. That's kind of the change that I want to bring to IBM in terms of how we talk about things. Absolutely. We will amplify it and we are not shy about where we are really, really good. But I want it through the lens of the people who are getting value.
- [22:20]
Christopher Mims
Yeah, enthusiasm, of course, that's super important for your stock price to make sure your employees feel like they're working for someplace that's continuing to grow. But that's all of tech, right? I mean, everybody's growing their revenues right now, if not their profits. However, a lot of that money's going into talent. You've seen Mark Zuckerberg credibly offer $100 million pay packages to potential AI researchers. Google, of course, they spent billions on a code completion tool. How do you compete where there's this overheated environment where everyone wants this talent. I jokingly asked Jerry, have you had $100 million offer yet? He said, no, but seriously, how are you going to hold on to talent?
- [23:02]
Arvind Krishna
Maybe a bit of experience helps here. This is not the first time we have gone through these. This happens every 10 or 20 years in the technology industry. The Internet era was identical. I remember it deeply. Back in 97 to 99 and 2000, all these same things happened when mobile came around. The same thing was talked about very early. Now with AI, the same thing is happening. No doubt it'll happen on Quantum. Also, the way you do it and the way you avoid sort of, I'll call it, with irrational reactions. Because some of these, I think are actually irrational reactions is that you have to have a deep enough bench and you got to ask the question, so why do these incredible people want to come work with you? And on Quantum, they come and work with us because they can work with an incredible team that has justifiably made more progress than anywhere else. So they'd rather be part of a winning team than part of a team that has a much higher chance of losing. I actually think that that is the same thing that happened in AI. The people who are in these collections were part of the winning teams. Well, now that they have won, in some sense, I would say maybe tongue in cheek. Those who are on the losing side think they can buy victory. History shows that usually does not turn out to be the case.
- [24:24]
Christopher Mims
Yeah, so I noticed at your research center there's a distinct lack of nap pods or ping pong tables. There's no slides between floors. It really felt like you're attracting serious people who want to work on serious, difficult problems. And how do you do that as opposed to attracting people with free kombucha on tap?
- [24:45]
Arvind Krishna
Well, we want people who want to work. Quantum, as you pointed out, has been a long journey. So let's talk about it as 10. Because 10 years ago is when we began to scale and go forward. But we knew it would be a 10 year journey. So we want to attract the people who have that grit in mind. That is something they can do at very few places. Because we are committed to solve these really hard problems. Because if you do, I'm saying if, then the price is massive. Okay? In a lot of places, their horizon is 1, 2, 3 years. That does not work. And so I have a huge focus on saying what are the one or two things? Because you can't do it across all things that have that kind of hardness. And then the price is significant and that brings value back to our shareholders, to all our employees at that point, because the quantum begins to scale and our consulting teams can take Quantum into clients. People are going to build quantum applications and a lot more will benefit. But we need to do that and actually to some sense, buffer the team that's working on it for those years until it reaches commercial viability.
- [25:54]
Tim Higgins
We're in this interesting moment, I think clearly we have these big names, the big upstarts, OpenAI and whatnot, but we also have some big names who are making comebacks. Right. I think if we go back 10 years, 15 years ago, Microsoft may have seemed like its best days were behind it, but it's really reinvented itself in a very dramatic way with cloud computing being its adoption of AI. And I think IBM also, a generation ago, may have seen like its best days were behind it. You were in the process of reinventing it for a new era. Do you see any parallels between kind of how IBM is doing it and what Microsoft has done? Is there a way to be successfully pivot to become a new behemoth?
- [26:43]
Arvind Krishna
Well, there are a few common principles just to make it straightforward. Number one, if you're overly wedded to your past and you find it really hard to let go, then effectively you're forcing your engineers and your sales teams to be very, very defensive in front of clients. And that is not usually a good practice. So if you think about Microsoft with Windows, or if you think about IBM with some of our legacy software from the 70s and 80s, that's a problem. But if I have incumbency, can I deeply understand what my clients want and give them what they will need for the future, even if they haven't fully realized it? Let's lean in there in addition to some of what we give them, and then don't be defensive. Be willing to give up some of what is not important. They're not. Being defensive, I think, is the biggest thing. I mean, Microsoft's unlock was when Windows was not the only thing they did. That turned out to be an incredible unlock.
- [27:45]
Christopher Mims
Yeah. Satya Nadella, head of cloud, became CEO and then they were off to the races. So if we take a big step back here, what is your long game? What's the bigger strategy here? Are you going to grow IBM until you're part of the Magnificent seven, the Mag eight? Yeah, yeah, Mag eight. Is IBM going to be in there? Of course there's still time for Tesla to drop out, so it can still.
- [28:09]
Tim Higgins
Be seven shots fired.
- [28:13]
Christopher Mims
But really, I mean, Are you going to just maintain by occupying your niche and Quantum? How, in other words, is IBM going to survive another 114 years?
- [28:23]
Arvind Krishna
Our goal is to grow. Grow means grow for our clients and grow for our employees. And that does mean revenue growth. It also is important to grow in terms of shareholder value because that is the commitment. We are a public company. We have to grow for our shareholders. On the s and P500, we are now, I think number 28 depends on the day. 27, 28, 29, 30. So let's say we've come up 30 spots over five years. I don't know. You can begin to extrapolate from there and say that was not maybe an accident, that was a strategy. And so where does that begin to go? Let me acknowledge that as you head up towards the. Instead of calling it the Max seven, let's just call it the top ten. Maybe it becomes tougher and tougher. You're reaching rarefied air over there. And it's not that those people are sitting still and not doing their own upward climb. Probably gives you enough to get a sense of our own ambition.
- [29:26]
Christopher Mims
Absolutely. Arvind, I appreciate you being so generous with your time and so generous with your insight.
- [29:33]
Arvind Krishna
Christopher, Tim, pleasure talking with the both of you. Thank you.
- [29:37]
Christopher Mims
We reached out to Microsoft, which declined to comment. Stick around. Tim and I break down what we just heard from IBM CEO Arvind Krishna Mims.
- [29:48]
Tim Higgins
I think we should tell the viewers, the listeners at home, that you were especially excited for this episode. Why was that?
- [29:55]
Christopher Mims
Well, technically, you booked this episode, Tim.
- [29:58]
Tim Higgins
Oh, did I?
- [30:01]
Christopher Mims
No, I was excited for this episode. And the simple reason was, as I started to dig in, I was surprised that a company that frankly, I had kind of written off as just slowly riding off.
- [30:14]
Arvind Krishna
Sorry.
- [30:15]
Christopher Mims
As a consultancy, you know, they turned out to be ahead in quantum computing, which was something that was like cold fusion.
- [30:24]
Arvind Krishna
Right.
- [30:25]
Christopher Mims
We had always been told it was just around the corner. Suddenly it was real and IBM, of all companies was doing it. That was a real mystery.
- [30:35]
Tim Higgins
It's super interesting, right? A former technological heavyweight. I mean, this was computers, right? But it's been struggling for decades, really, in a lot of ways, until this hybrid cloud strategy consulting. And his appointment in 2020 was a really big, big moment of change.
- [30:55]
Christopher Mims
But I think that you brought to this your usual and necessary skepticism. Right. So it was interesting to hear you say, why should we believe that Quantum will be any different? I'm just curious where that skepticism came from. I mean, beyond just your childhood.
- [31:14]
Arvind Krishna
Right.
- [31:14]
Tim Higgins
Just kind of how I was Brought.
- [31:16]
Christopher Mims
Up your personality, your DNA.
- [31:19]
Tim Higgins
Well, I mean, IBM has been on the vanguard of the next big thing before, right? With, with AI. They did such a good job selling us on Watson. I mean, you thought Watson was going to be your best buddy, right? Solving all the world's problems.
- [31:33]
Christopher Mims
IBM's made a lot of promises. Watson has been a decades long egg on its face moment for the company. It was one reason that I had kind of written it off because I knew pretty intimately how early they were to AI and also how they had kind of made the wrong bet. I mean, I think at a fundamental level they bet on a set of technologies that just got superseded by things that were happening at places like Google, you know.
- [32:00]
Tim Higgins
So we ended the conversation asking whether IBM can be part of the Mag 7.
- [32:05]
Arvind Krishna
You know, I don't know if it'll.
- [32:06]
Tim Higgins
Kick out Nvidia or Tesla, you know, you decide. But is making this big bet now on Quantum, will that help Big Blue do things differently this time compared to its Watson experiment?
- [32:23]
Christopher Mims
I think that IBM has the potential to grow considerably in the short term. Not because of Quantum. Right. If we're talking about the year 2100 and we've fundamentally changed the way we do all of computing. Yeah, maybe whatever it's called, then they could see a lot of growth at that point.
- [32:45]
Tim Higgins
But right now that growth is because of hybrid cloud and consulting. As we talked and since we recorded this interview in late July, IBM is ranked somewhere between 33rd and 40th largest company by market cap in the S&P 500. So still quite a bit of ways to go if it's ever going to catch up to the Mag 7.
- [33:07]
Christopher Mims
Yeah, but if and when that happens, you can say you heard it here first on bold names.
- [33:13]
Tim Higgins
Bold names where bold things happen.
- [33:18]
Christopher Mims
I don't know about that kicker too.
- [33:21]
Tim Higgins
Let's workshop that a little bit more.
- [33:23]
Christopher Mims
And that's Bold names for this week. Our producer is Ariana Asperu. Our video producer is Kasha Brusalian. And our fact checker is Aparna Nathan.
- [33:35]
Tim Higgins
Michael Lavall and Jessica Fenton are our sound designers. Jessica also wrote our theme music. Our supervising producer is Kathryn Millsop. Our development producer is Aisha Al Muslim. Chris Sinceley is the deputy editor and Falana Patterson is the Wall Street Journal's head of news audio.
- [33:54]
Christopher Mims
For even more, check out our columns on WSJ.com we've linked them in the show notes.
- [34:01]
Tim Higgins
I'm Tim Higgins.
- [34:02]
Christopher Mims
And I'm Christopher Mims. Thanks for listening.
- [34:09]
Kelly Cavagnaro
Hi, I'm Kelly Cavagnaro, managing Director Head of North America Institutional Distribution At Janice Henderson Investors we believe working together is the way to work better. Like combining your portfolio plans and our in depth strategy. Your valued assets and our valuable insights. Your mission and our vision. Working in harmony to seek the right investment opportunities. Janice Henderson Investors Investing in a brighter future together.