Davos 2026: Arm CEO Rene Haas 1/23/26

Summary

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Squawk Pod: Davos 2026 – Conversation with ARM CEO Rene Haas

Podcast: Squawk Pod
Episode: Davos 2026: ARM CEO Rene Haas
Date: January 23, 2026
Host Panel: Becky Quick, Joe Kernen, Andrew Ross Sorkin
Notable Guest: Rene Haas, CEO of ARM Holdings
Reporter/Producer: Cameron Costa

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Episode Overview

In this special episode from the World Economic Forum in Davos, Switzerland, ARM CEO Rene Haas sits down with the Squawk Box anchors to discuss the company’s pivotal role in the rapidly-growing AI ecosystem. The conversation covers ARM's business model, the AI era’s unprecedented demand on semiconductor supply, energy efficiency, future breakthroughs in artificial intelligence, and big-picture questions about the singularity and societal change.

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Key Discussion Points & Insights

1. ARM’s Omnipresence and Business Model

• ARM technology powers an extraordinary range of devices, from smartphones and data centers to cars and home appliances.
• ARM operates on a licensing model: they provide CPU IP (Intellectual Property) to chipmakers, who in turn manufacture and deploy chips in end products.

Notable Quotes:

• "Enough ARM chips have been shipped to cover every person who's ever lived on the planet and then some." – Rene Haas (03:03)
• "ARM is… referred to as the Switzerland of the semiconductor industry. It would be hard...to find a company that doesn't use ARM." – Rene Haas (03:40)

2. Energy Efficiency and AI Workloads

• AI’s voracious appetite for compute has placed new strains on energy infrastructure and data center operations.
• ARM’s focus continues to be on highly energy-efficient processors, which are increasingly critical as AI models grow larger and inference moves to edge and wearable devices.

Notable Quotes:

• "As more complex AI gets, energy efficiency is everything, which we’re really good at." – Rene Haas (04:28)
• "We're also in small devices like wearables that consume less than a watt of power…critical to be able to run those AI workloads in small devices such that we're not consuming so much energy in the cloud." – Rene Haas (04:58)

3. Semiconductor Supply Chain and Data Center Scaling Challenges

• Demand for compute power is causing shortages in memory, wafers, and even broader infrastructure elements like electricity and transmission lines.
• Progress has been made in addressing supply bottlenecks, but moving energy to where it’s needed (for example, establishing transmission lines for new data centers) remains a substantial challenge in the U.S.

Memorable Segment:

• "[In] the US we actually have a fair bit of energy, but it's actually getting that energy to the places where the data centers need to be—transmission lines that require contracts and easements…our industry never had to worry about." – Rene Haas (06:12)

4. AI Breakthroughs and Domain-Specific Progress

• The panel discusses the potential for groundbreaking advances that may reduce the need for raw compute, such as domain-specific AI architectures or energy-efficient memory designs.
• Haas is optimistic about such innovations but suggests that big, domain-specific leaps are more likely than a single all-encompassing breakthrough.

Notable Quote:

• "There could be some innovation in that area that could be a new chip architecture, a new memory architecture, less energy…AI models…will become very domain specific, specific to certain areas and problems." – Rene Haas (07:11)

5. AI, Creativity, and the Inevitable Singularity

• The discussion pivots to existential and societal questions:
  • Will AI replace workers?
  • At what point does AI begin to invent, create companies, design products?
  • When does the singularity (machine intelligence at/par with or beyond human intelligence) occur?
• Haas is convinced that it is not a question of "if" but "when" the next level of AI creativity emerges, citing the accelerating pace of innovation.

Memorable Quotes:

• "Does AI start to replace workers? Does AI start to invent? At what point does AI create? What is the next product?...It is an area to sort of explore in your mind." – Rene Haas (07:53)
• "It's not an if question, it's a when question. This will happen, right? If you look at the level of innovation in the last 10 years compared to the previous 50 or hundred, it will get there." – Rene Haas (08:36)
• "In my mind, we don't know after that, we have no idea. That's why it's called a singularity." – Joe Kernen (08:52)

6. Self-Driving Cars and Predicting the Timeline

• Using autonomous driving as an analogy, the group discusses "conelike" risk—the uncertainty of predicting how soon major technological milestones will occur.
• Haas believes full self-driving is simply a matter of generational change and inevitability.

Notable Quote:

• "Self-driving cars as a constant is going to happen. There will be a generation that will look at standing parking garages and say what was that generation thinking? That they actually had cars that sat idle for 23 hours of a day." – Rene Haas (09:29)

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Timestamps for Critical Segments

• ARM’s Ubiquity in Tech – 00:49–01:20, 03:03–03:40
• Energy Efficiency Focus – 04:28–05:27
• Supply Chain Disruptions & Data Center Power – 05:27–06:43
• AI Models, Innovation, and Future Risks – 06:43–08:52
• Singularity, AI Creativity, and Societal Change – 08:52–09:29
• Self-Driving Cars & Future Generation’s Perspective – 09:29–09:42

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Memorable Moments & Notable Quotes

• ARM’s reach:
  "ARM is…referred to as the Switzerland of the semiconductor industry."
  – Rene Haas (03:40)
• On energy and AI:
  "As more complex AI gets, energy efficiency is everything…”
  – Rene Haas (04:28)
• On moving energy, not just producing it:
  "It's actually getting that energy to the places where the data centers need to be..."
  – Rene Haas (06:12)
• On AI’s future:
  "It's not an if question, it's a when question. This will happen."
  – Rene Haas (08:36)
• On the unknowable future:
  "In my mind, we don't know after that, we have no idea. That's why it's called a singularity."
  – Joe Kernen (08:52)
• On self-driving's inevitability:
  "There will be a generation that will look at standing parking garages and say what was that generation thinking? That they actually had cars that sat idle for 23 hours of a day."
  – Rene Haas (09:29)

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Tone and Style

The exchange is insightful, engaging, and at times lightly humorous, with the hosts pressing gently and Haas providing clear, forward-looking answers. The conversation balances industry specifics with big-picture speculation—a mix of technical acumen and vision about the future of AI and technology.

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Summary

This episode provides a rare window into the infrastructure enabling today’s AI explosion, and Rene Haas articulates the massive (but mostly invisible) reach of ARM’s technology. From the inside, Haas’s "when-not-if" stance on technological leaps underscores a conviction that innovation—particularly in AI—is speeding past historical benchmarks. The group’s musings on the singularity and self-driving cars frame a larger question: how much of our future remains in the hands of technologists, and how much in the hands of society at large?

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Transcript

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[Rene Haas]

Nvidia Grace Blackwell that's all ARM Apple's iPhone, that's ARM Samsung's Galaxy Phone, that's ARM Pixel's Google phone, that's ARM Microsoft shipping service Tablets based on ARM ARM.

[Cameron Costa]

Holdings CEO Rene Haas at the World Economic Forum in Davos, Switzerland. His position in the AI ecosystem As the licensor of the CPUs that build data centers, iPhones, even wearable tech, it.

[Rene Haas]

Would be hard to find a company that doesn't use arm.

[Cameron Costa]

His vision for innovation is one of the building blocks of AI.

[Rene Haas]

Where does AI go right? Does AI start to replace workers? Does AI start to invent? At what point does AI create? What is the next product?

[Cameron Costa]

Plus the potential for AI to invent new AI, new companies? Haas says it is only a matter of time.

[Rene Haas]

The level of innovation in the last 10 years compared to the previous 50 or the previous hundred. It will get there. The question is when?

[Cameron Costa]

I'm CNBC producer Cameron Costa. Squawkpod reports from Davos 2026 ARM Holdings Rene Haas begins right now. For the past couple of years, the hot topic at the annual World Economic Forum has been AI. Joe Kernan, Becky Quick and Andrew Ross Sorkin have spoken to many leaders and regulators in the space. Execs from anthropic OpenAI meta those conversations will all be on your Squawk Pod feed if you're interested. This next conversation, though, it's with one of AI's builders. ARM Holdings CEO Renee Haas sat down with Joe, Becky and Andrew on our outdoor set in the snowy Swiss town of Davos to talk about the big world that he is building.

[Becky Quick]

Renee, thank you for being with us today. It's really a pleasure to have you here.

[Rene Haas]

Good afternoon.

[Becky Quick]

I I know what you all do is a little different than what so many others do because you all are in the licensing business, but I saw a statistic that blew me away something like four chips for every human on the Planet was sold by ARM in the last year. Is that accurate? Am I getting that statistic correct?

[Rene Haas]

Yeah, something like that. There's some crazy statistics that says enough ARM chips have been shipped to cover every person who's ever lived on the planet and then some. What we do is a cpu. It's a compute platform that's the heart of just about every device you can think of, whether it's smartphones, data centers, automobiles, washing machines. Our business model is licensing. So we license that CPU intellectual property to someone who makes a chip. That chip goes into the device. A lot of devices end up shipping.

[Becky Quick]

So how should we think about you in this really competitive chip space at this point? Who's your partner? Who are you competing against? How does that work?

[Rene Haas]

It's ironic that we're in Switzerland. ARM is, you're neutral, referred to as the Switzerland of the semiconductor industry. It would be hard, Becky, to find a company that doesn't use army. Nvidia, Grace Blackwell, that's all ARM. Apple's iPhone, that's ARM. Samsung's Galaxy phone, that's ARM. Pixel's Google phone, that's ARM. Microsoft shipping surface tablets based on ARM. So we supply our CPU IP to everybody in the industry. And the reason that is important is that a cpu, which is the digital brain of every modern device, everything needs a cpu. So as a result, ARM is pretty, pretty much everywhere.

[Becky Quick]

And what do you think when you sit back and look at these wars that do you care how this competitive landscape plays out? Do you just figure it doesn't matter, you're going to be there no matter what?

[Rene Haas]

To some extent. I think right now it's an amazing time in our industry with everything going on. Obviously with artificial intelligence, it's hard enough to talk about it. We see artificial intelligence workloads running everywhere, whether it's inside the data center or in your smartwatch. And that's a huge opportunity for ARM because as more complex AI gets, energy efficiency is everything, which we're really good at. And that's an area we're quite focused on.

[Becky Quick]

So what is your latest advancement in that exact area in energy?

[Rene Haas]

Yeah, so we do the low powered processor. That's the heart of the Grace Blackwell platform. And Jensen then also talked about Vera Rubin, I think at CES a couple of weeks ago. That's all arm that uses six times the number of ARM CPUs in the platform that the previous platform did. But we're also in small devices like wearables that consume less than a watt of power. And I think over time it's going to be very critical to be able to run those AI workloads in small devices such that we're not consuming so much energy in the cloud.

[Becky Quick]

The rush that's on right now for any of the data centers that are trying to make sure they have enough electricity, that they have enough copper, that they have all of these different ingredients. And does that impact you at all? Because it does impact your customers, sure, yeah.

[Rene Haas]

Anybody who's in the semiconductor supply chain is impacted by this. Whether it's not enough memory, not enough wafers, not enough turbines, to some extent, we're all impacted by it. But what's happening is because the amount of compute that's required is just so large. That's why you're still seeing pretty large numbers being reported by all the chip guys, just because the volumes are are so darn big.

[Becky Quick]

Andy Jassy told us this morning that the whole idea of the shortage for energy still exists for data centers, but it's better than it was 18 months ago. Would you agree with that?

[Rene Haas]

I would agree that it's better than it was 18 months ago. But one of the problems that we have, particularly in the US is not so much energy, because in the US we actually have a fair bit of energy, but it's actually getting that energy to the places where the data centers need to be, transmission lines that require contracts and easements and all the things that our industry never had to worry about. Some small village having to get an easement to get a new transformer cut across county lines. So, yes, some things have gotten better, but still the scaling problem exists.

[Andrew Ross Sorkin]

You know, last year we had this deep seek moment actually here in Davos where everybody had a freak out and said, oh my goodness, the Chinese not only are able to create a large language model, but they're able to do it with less processing power than it seemed everybody else and then there were questions about whether they were stealing stuff and this and that. But is there any concern that you have that there could be such a great technological breakthrough? I mean, this would be great in one way, but maybe terrible in another. If you're in the chip processing business.

[Rene Haas]

From an ARM standpoint, I'd be hard pressed to think of a terrible outcome. That being said, though, I think there will be some innovation around these models, language models, for example, which are very good at taking text and providing words. Are they experts at science? Are they experts at drug discovery? Are they experts at certain things? The truth is not known yet, and I think there could be some innovation in that. Area that could be a new chip architecture, a new memory architecture, less energy. I think what's going to happen over time with these AI models is they'll become very domain specific, specific to certain areas and problems which will be good for the industry, but but may change who we think today's winners and losers are.

[Becky Quick]

What do you worry about then? If that's not a big issue at.

[Rene Haas]

The end of the day, one of the things that we think about more broadly is where does AI go, right? Does AI start to replace workers? Does AI start to invent? At what point does AI create? What is the next product? Could you create an AI that says, create me a brand new company with brand new workers, et cetera, et cetera? I don't know if I worry about it so much, Becky, but it is an area to sort of explore in your mind.

[Andrew Ross Sorkin]

It's predestined that that happens. Meaning we all talk about it as if it's just a scaling law, that if you keep adding more energy and more chips to this, that we will ultimately get there. Is there any, by the way, there are other people, Ilya and others in the large language model world who say actually we need a major breakthrough to get there. That you're actually just throwing processing power at the problem is not going to get you there.

[Rene Haas]

It's not an if question, it's a when question. This will happen, right? To the extent that we have been able to solve technology problems to the level that we have, if you look at the level of innovation in the last 10 years compared to the previous 50 or the previous hundred, it will get there. The question is when, not an if.

[Joe Kernan]

In my mind, we don't know after that, we have no idea. That's why it's called a singularity. We have no idea what comes after. I really don't think we do.

[Rene Haas]

I don't know how we could answer that question right when machines start to think and create an event to the level that humans do. And you get into questions of consequences.

[Andrew Ross Sorkin]

But the when part does matter because for a long time we talked about self driving cars, for example, example. And we're still, we're there, but we're.

[Joe Kernan]

Not there kind of there.

[Andrew Ross Sorkin]

We're pretty much there sort of and sort of not.

[Joe Kernan]

I don't want to get there.

[Andrew Ross Sorkin]

And so the question is, I like the driving is, you know, is 2030 your year? Is 2040 your 2050 is your year? And if. And there's. That's a, that's a big cone of risk in between there's a big cone.

[Rene Haas]

Of risk, but self driving cars as a constant is going to happen. There will be a generation that will look at standing parking garages and say what was that generation thinking? That they actually had cars that sat idle for 23 hours of a day.

[Becky Quick]

Renee, thank you for joining us today. Rene Haas.

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Thank you for listening to this special Squawk Pod reports from Davos. This is just one of our many interviews from from the World Economic Forum and I promise it's worth following Squawk Pod wherever you're listening now. Squawk Box is hosted by Joe Kernan, Becky Quick and Andrew Ross Sorkin. Squawk Pod is produced by me, Cameron Costa and Zach Felici. A big thanks to our editor, Julie Tras. Have a great week. At Capella University. We believe accessible education can make a difference. That's why we offer scholarship opportunities to all eligible students. Un futuro diferente estamma serca de lo que cres con Capella University. Learn more at Capella Eduardo.