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A
Hi, everybody. Tune in to this short version of the podcast, which we do every Friday. For the long version, tune in on Wednesdays.
B
Hi, everybody.
A
I'm Nicola Tangen, the CEO of the Norwegian Sovereign Wealth Fund. And today I'm in particularly good company because I'm with Arvind Krishna in New York, and Arvind is the chairman and CEO of IBM, one of the most iconic technology companies in the world. Arvind has been with IBM for over 35 years and became the CEO in 2020 and have since orchestrated one of the most striking turnarounds in big tech. When he took over, IBM had been declining for years and today is growing faster than it's done for a long time. So, Arvind, a warm welcome.
B
Thank you. Nikolaj, it's always good to talk to you.
A
Absolutely. Now, a lot of people still think that IBM is kind of a company from another era, and you have changed that. So today, what does IBM do?
B
IBM is largely a hybrid cloud and AI software company. We have made the transition to. That's almost half our total revenue. We have another third that is in consulting. And we try to help our clients transform for the current era of digital and AI. And then we have about 20% that is hardware. I realize many people think that we are largely a hardware company, but that is just a fifth of the company. A very important piece, but a very small piece.
A
When you took over as a CEO, the IBM had been declining for some time. What was your diagnosis?
B
I always like to sit back and think, what are your strengths and what are your weaknesses? So as I talk to our own team and as I talk to clients, it comes out that we were trusted, but we were considered to be part of the past, not necessarily the future. So my diagnosis was, you have to do things that are relevant for people's future. They're not always the biggest revenue in a month or in three months or in one year, but they become the big revenue over the next many years. So we began to say, what are we good at? And then, can we double down? Can we double down on helping people transition towards a hybrid cloud? We were strong believers that sovereignty would remain important for many, many years to come. And so you double down on the portfolio that helps them do those things. And back in 2019, I was convinced that AI would be big. It took another three years for the world to wake up to that.
A
What made you so convinced at the time?
B
Data is going to overwhelm you and value is going to be derived from data. What can unlock the value from that much data. The only technology we knew was AI.
A
But when you talked about these sort of technology shifts, how would you compare the AI advancements compared to those shifts?
B
I think it's bigger than mobile and it's bigger than cloud. It's probably in the same category as Internet. If you go back to 1995. I use 95 because you are much more.
A
I mean, many clever people say it's like 10 times the Internet. But you don't think it's that.
B
No.
A
And you are, and you are very clever, by the way. I should mention that. Not that it needs explaining, but our mutual friend Malcolm Gladwell said that you were the cleverest person he had met.
B
I don't know whether I'm the cleverest, but I'm older than many and I have been around a few of these. The Internet to me was fundamental if you think about it, because many people don't realize the scale of global business that happens today is because of the Internet. The ability to move work in technology from country to country is because of the Internet. The fact that a small producer, be it in Europe or be it in Africa or in China, in can sell and be part of the supply chain for a global corporation anywhere in the world is because of the Internet. If I look at that, the Internet has had a massive impact. The direct revenue even to the technology providers is measured in the trillions today. The rise of all the social media companies could not have happened without the Internet. The rise of cloud could not happen without the Internet. If I include all those as the impact of the Internet, then AI is going to be in that category.
A
But do you think you are biased in your assessment of AI given that you have tried before and failed?
B
The fact that we tried failed, but remained committed and I made the bet on AI in 2019 again before the advent of ChatGPT says no, I don't think we are biased or jaded because you can imply that in your question. I actually think it's going to be very, very powerful. But it's in the same.
A
But tell us about. I mean, you tried with Watson, right? Just tell us about Watson.
B
I think that Watson was the right goal.
A
What was it?
B
So in 2011 we wanted to prove that AI can do and solve problems that were unimaginable at that time. People couldn't imagine that you could do natural language question and answers on kind of a gray area using AI winning the game Jeopardy, which had these questions in English but with all kinds of hidden puns and language. And that had to be Interpreted, not just the black and white question proved that AI can do those things, then you could say, but you failed. Why did you fail? The reason is we took that technology and we said, we want to construct monolithic applications. And we unfortunately picked the vertical. That is the hardest health. That was the mistake. If we had taken it and said, let's use it to help corporations get better, let's use it to let their customers get better customer care, let's use it to digest all the documents that enterprises have, I think we would have been five years ahead of where we are today on AI. But it would have been a long journey because the technology then was still what I call bespoke. What I call bespoke is yes, AI worked, but it worked when you had one use case with one corpus of data. Today's AI actually can do many use cases. So that's a big advantage. Two, you don't have to relearn. If some of the data changes, you can add the new data and add to it. Those two things make it much more industrial scale today than the one from 10 years ago. And that is why we didn't succeed then. But I do believe that we will succeed this time around.
A
Well, let's spend some time on quantum computing, which is one of your big bets, right? For somebody who listens to this program, who is not very technical in simple terms, what is quantum computing?
B
So quantum computers at one level, and I'll just geek on the science for 10 seconds and get off, are trying to harness properties of quantum mechanics to do a new kind of math. That's the simplest way to explain it. So if I think about normal computers, they do arithmetic, you know, think of high schoolers, arithmetic and algebra, that's what they do. But they do it at incredible speed. So that looks remarkable. Then we can say, what do GPUs do? Because with the advent of AI, GPUs have come into the parlance. GPUs do matrix mathematics. Let's just put it that simply. But matrix math unlocks a lot of problems that would be 10,000 times slower to do on normal computers. Such as, for example, if I want to do an LLM, to do an LLM on a CPU would probably be so slow, none of us would care. But you can do these large language models. You can recognize, is this a cat or is this a dog, or is this a human being in a photograph is kind of what matrix math unlocks.
A
So let's say now we fast forward. What do we think? When will we have them?
B
2029. Right.
A
Okay.
B
Quantum computers.
A
So let's say to be safe, we're now, five years from now, we have this big quantum computer in this room. Now what are you and I going to do with it? What's the stuff we can do then?
B
I think the first three use cases, the first one I think nobody debates, is going to be in the world of materials. So you look at pieces of materials. What do you mean by materials? Would I like a better coating so that things don't corrode? Example aircraft wings or rivets or pipes that carry oil? That's pretty important. Or could I design a better pharmaceutical drug because we can do things with molecules and be able to predict the properties as opposed to have to do a wet lab experiment? Or can I come up with a better fertilizer than the current very energy inefficient fertilizer that is there, or one that I'm getting excited by because our team just showed that you can predict magnetic properties of materials using quantum computers. Well, if I can do that, is there a possibility? And I'm calling it a possibility because we're still three, four years away to have a better magnet. And as we know, you need magnets for electrification, for EVs, for lots of things. So those are the first category. The second category I think is going to be around financial risk. How can we price something better knowing what we know? So the way we do it today, we kind of use data that's a week old or a day old, and then we try to guess during the day what it should be. But if a quantum computer could price some of those things in milliseconds, then that gives you an advantage in the financial world to be able to price complex instruments or derivatives or bonds, as some of our clients have begun to do during the day. And the third is going to be in the area of optimization. And by optimization I mean things like can we do a better route plan? Could we somehow attack the problem that 30% of all truck miles and containers are empty as opposed to used? And that's because we use very simple routes, because it's just too hard to do a complex route for all these things. So those are problems that I think quantum computers are going to unlock in the first few years.
A
You have something called getting fired mentality. What does that mean?
B
Fifteen years ago, I walked into the office of a mentor of mine at 6:30 in the morning and I was kind of frustrated. I said like, look, you know, I really believe that I need to say these things. But I'm afraid that if I say them, somebody will want to try to fire me. And this person turned on and told me, arvind, you should live in the pleasure of being fired. And I looked at me, he said, that doesn't mean that you always pick a fight. It doesn't mean that you just make disruptive things for the sake of it. But if you are living in the pleasure of being fired, that means you're not afraid of being fired. That means you'll do the right thing. And if you have confidence in your abilities, why does it matter? And that was truly freeing. And I encourage people to think like that and to be like that, and I think it really has been very powerful.
In Good Company with Nicolai Tangen
Date: May 8, 2026
In this highlight episode, Nicolai Tangen, CEO of the Norwegian Sovereign Wealth Fund, sits down with Arvind Krishna, Chairman and CEO of IBM, in New York. The conversation focuses on Krishna’s leadership approach, the remarkable transformation of IBM under his tenure, the company’s technology bets—particularly in hybrid cloud, AI, and quantum computing—and the philosophy guiding his decisions. Listeners gain insight into IBM's shifting identity, lessons from past failures like Watson, the transformative potential of quantum computing, and Krishna’s personal leadership mindset.
Timestamp: 00:46 – 01:25
“IBM is largely a hybrid cloud and AI software company. ... We try to help our clients transform for the current era of digital and AI. ... hardware ... is just a fifth of the company.”
(Arvind Krishna, 00:55)
Timestamp: 01:25 – 02:22
“You have to do things that are relevant for people’s future. ... They become the big revenue over the next many years.”
(Arvind Krishna, 01:36)
Timestamp: 02:22 – 06:21
“Data is going to overwhelm you and value is going to be derived from data. ... The only technology we knew was AI.”
(Arvind Krishna, 02:24)
“I think it's bigger than mobile and it's bigger than cloud. It's probably in the same category as Internet.”
(Arvind Krishna, 02:43)
“If we had taken it and said, let's use it to help corporations get better, ... I think we would have been five years ahead of where we are today on AI. ... But it would have been a long journey.”
(Arvind Krishna, 05:19)
Timestamp: 06:21 – 10:27
“Quantum computers ... are trying to harness properties of quantum mechanics to do a new kind of math. ... Those are problems that I think quantum computers are going to unlock in the first few years.”
(Arvind Krishna, 06:37, 10:20)
Timestamp: 10:27 – End
“If you are living in the pleasure of being fired, that means you’re not afraid of being fired. That means you’ll do the right thing.”
(Arvind Krishna, 10:41)
On IBM’s AI Failures and Second Chances:
“We tried, failed, but remained committed ... I do believe that we will succeed this time around.”
(Arvind Krishna, 04:14, 06:09)
On the Scale of the Internet:
“The Internet to me was fundamental ... The rise of all the social media companies could not have happened without the Internet. The rise of cloud could not happen without the Internet. If I include all those... then AI is going to be in that category.”
(Arvind Krishna, 03:11 – 04:07)
Host’s Admiring Aside:
“Our mutual friend Malcolm Gladwell said that you were the cleverest person he had met.”
(Nicolai Tangen, 03:00)
The conversation is candid, insightful, and forward-looking. Tangen’s questions are direct but inviting, while Krishna’s responses balance technical explanation with accessible analogies. There is mutual respect and the occasional lighthearted moment, underlining the dynamic yet thoughtful tone of the episode.