Hello, everybody. Welcome to Davos, Switzerland, and welcome to the 2026 Annual Meeting of the World Economic Forum. We are happy that you’re joining us live for this panel.

And my name is Andrew McAfee. I’m a scientist at MIT. I’ll be the moderator today.

And we’re here at Thursday. We’re close to the end of the Annual Meeting 2026. And I can assure you that the topic of this panel has been top of mind throughout the annual meeting this year.

It’s been probably one of the most actively discussed topics here, certainly because of this remarkable surge of progress we’re seeing with AI, but for lots of other reasons as well. I think perhaps the dominant conversation this year at Davos has been exactly the subject of our panel today, which is converging with technology to win. Now obviously, we need to define what win means, and that can mean different things to different people in different parts of the world.

We probably need to talk a little bit about which technologies are top of mind, but this is the topic at Davos 2026. It’s at least in anyone’s top two or three list of topics. The good news is that we have people who are finally going to answer the question.

In 45 minutes, we’re going to nail this. And the reason I say that with confidence is because of the panelists that I have the honor to share the stage with. I’m sitting next to His Excellency Abdullah AlSwaha, who is the Minister of Communications and Technology for the Kingdom of Saudi Arabia.

Next to him is a person who I personally have learned a lot from, Laura D’Andrea Tyson, is an economist at the University of California, Berkeley. And you might have heard that there’s a lot of technological innovation happening in and around the Berkeley area in Northern California. Luckily, Laura knows all the secrets, and she’s going to share them with us.

Next to her is Vimal Kapur, who is the Chairman and Chief Executive Officer of Honeywell, a high-tech company based in the United States. And last but absolutely not least is Sassine Ghazi, who is the President-Elect of Saudi and CEO of Synopsys, a technology company that you might not have heard of, not as much of a household name, but critically important because they are a critical link in the semiconductor manufacturing and innovation supply chain.

I think without you all, we don’t have the chips that are powering the AI revolution. So first of all, thank you for that. And second of all, how the heck are you doing it?

But I think, Laura, if we could start with you. Please.

Okay. Happy to do it.

Because economists like yourself have been studying this question for a long, long time. What is it that allows a region or a country to build a technology ecosystem that converges to a place that would make everybody happy? In other words, it innovates like crazy.

It generates a lot of value for customers, a lot of wealth. It provides good jobs for a lot of people. Leaving modesty aside, your part of the world, California, is almost certainly the world leader in that.

If you could give us your version of what happened in Northern California to make that work, and then more broadly, because that’s not enough. More broadly, what’s the secret sauce for getting the environment right to let this kind of magic happen? Industrial policy is a term that I know that you use.

Some people do like it, some people don’t. But there’s no, I think everyone here would agree, there’s no way that we get these fantastic converging tech ecosystems without the government involved doing the right things. I know you have beliefs about what those right things are.

We’d love to start with those.

Good heavens. That was a long set of questions, in fact. I’m going to make a contrast.

Let me make a contrast. The contrast between the kind of model that is behind the innovation technological revolutions in the United States, particularly around Silicon Valley. But I also want to talk about China.

Because if you… I’ve been working for the past year on the battery and EV industries. And here’s where a country, through an industrial strategy, it was a country that set the industrial strategy.

And then the country, over many years, it wasn’t like it didn’t happen overnight, did a number of things to create the ecosystem with the private sector. Most of the producers of EVs in China are private companies. But it actually developed a whole ecosystem, because it had a strategy to be a major player as a nation in EVs and batteries.

So that’s a quick summary of China. Of course, in the US, it really has been very much driven by basic science, by the relationships between companies and universities. I think synopsis, right, isn’t synopsis connected?

Yes, to engineering faculty at Berkeley. We know that we have Google, and if we think about the history of Google, where does it come from? It’s basically basic science support for students and faculty at a university, which leads to a breakthrough.

The breakthrough becomes something which has a market value. It’s taken out. It becomes a major, what, a major company of the world.

But it started that way. And it started that way with also people willing to take risk. So the issue of risk capital—I hear a lot about this in the situation that’s going on in Europe, because there’s a lot of discussion about how Europe has many technological strengths.

But if it develops an innovation, frequently what it does is it looks for the risk capital, the private equity capital, the venture capital in the United States, because that market is so deep for financing it.

So I want to emphasize in the market model the link with universities, the link with finance, the link with risk-takers. Now I’m going to say one other thing, because if you look back in history to the U.S., the U.S. has— not really had industrial policy, but it has had industrial policy related to defense.

So a lot of the original breakthroughs were coming out of DARPA or DARPA-funded research that would occur at a university. So we did have the support of the Defense Department and the willingness to take risk in defense issues, and that remains, by the way. We used to have a lot of capital on the basic science side coming into, I would say, just medical research, cancer research, the development of new drugs.

That drug pipeline that comes out of the United States, if you go back, you sort of see the support for basic science. So I would say those are the features of the U.S. system.

In the Chinese system, I really want to say that it is the long-term, a nation, not a company, has an industrial strategy. The nation decides that it wants to pursue competitiveness in this industry. It wants to pursue technological progress in this industry.

It uses a variety of things, not access to venture capital, but essentially access to state capital.

Hold on, hold on. In particular, USVC was incredibly important for the Chinese tech ecosystem.

Oh, yeah. No, no. What I’m saying is that also in China, there is financing that is coming from the public sector.

That’s all. It’s not to say that venture capital at a certain point. If you think about, for example, AI, what China is pursuing at this point is really all of these amazing edge applications, and those edge applications are being financed by the private sector, by venture capitalists, who are basically saying we can sell something to Tencent, and Tencent will actually transform what it does.

So I really was thinking more if you have a vision of a particular industry and the industry is nascent, it’s not yet developed, okay, then having a public sector funding which is essentially was part of China’s strategy in EVs, but switching over time, switching over time to private sector.

Am I hearing right? You’re doing a lovely job of saying that we have two very large, very successful tech ecosystems on the planet.

Yes, right now, and they developed in different ways.

I’m hearing that you, am I hearing correctly that you kind of prefer the Chinese one?

No. It’s not that I prefer the Chinese one. I think if you, I thought to a certain extent, one of the words in the title of this was industrial strategy.

To the extent that you’re talking about industrial strategy, that is a national goal, and then you have to think about are you equipped in your system to pursue the national goal. Okay, and so for example, we have had now in the US, we had for a while, we decided we needed for national security reasons to have a real ability to produce high-end chips in the United States. It’s a national security industrial strategy argument.

We used a whole bunch of policy to get that done. We now have some production in the United States. Now the problem, I would say, is we have production which is going to be pretty high cost.

So keeping that competitive internationally is something we haven’t solved.

Great. I want to make this concrete. Minister AlSwaha, you are responsible for formulating a national strategy for the kingdom.

My guess is that you and your colleagues have scanned the history and the current landscape of technology. ecosystems, I’m sure as you’ve done that, there are two that stand out. There’s the US, there’s China.

Is what you’re doing more like one of those or the other? Are you a blend? Are you trying to find a third way?

Where’s your thinking on this?

Andy, if we take a step back and we had the pleasure of collaborating during the digital age under the guidance of His Royal Highness, how we can diversify our economy, and by the way, we’ve achieved 56% diversification of an oil GDP remarkably quickly ahead of the 2030 mark, but really it helped humanity overcome the over, you know, the great reset with the great resilience.

And that’s what the digital fabric gave us. And the investment thesis for the kingdom was very simple. If we double down on talent, technology, and build trust with partners, we can achieve success.

And we’re following the same blueprint for the intelligence age, because the intelligence age would need two things, the great acceleration, but the great adoption. And it’s not only important that you focus on the supply side of the world, because that’s going to trigger a couple of winters and bubbles, but it’s the adoption. And that’s why the kingdom, we have energized the industrial age.

It’s only natural that we energize the intelligent age. Last year, we clocked $0.11 per a million input-output tokens. It’s only natural for us to become the most AI-enabled nation in the world.

We’re doubling down on generative AI in healthcare. With UC Berkeley, and I’m going to share some success stories shortly, we’re doubling down on agentic AI, both in the public and private sector, where every private and public worker is going to have an agent to infuse that 10X productivity.

And we have delivered the first physical AI deployment when it comes to a fully robotics heart transplant done within our national hospitals. Last but not least is how we can become, really, the test bed for innovators and investors. Saudi last year, Andy, had the largest investment ticket in AI, and the largest success story, a Nobel Prize winner, a Saudi-American, Professor Omar Yaghi, working with UC Berkeley and our national labs, using AI to create new chemistry, metal-organic frameworks, effectively a sponge with the right pore size to capture water from air and carbon.

And when it comes to the largest ticket, you can ask Jonathan Ross, who was introduced to the world two years ago, on Leap, the largest tech event right now in the region, and by a mile from a number of other tech events, but on stage, how the kingdom is tackling the memory wall, how we’re doubling down on memory on the chip, next to the chip, and near to the chip.

And we have demonstrated that 11 cents per million input-output token, energizing Aramco, who wrote the first P.O. for Jonathan back then, how we could deliver bottom-line efficiency with a billion dollars last year, and this year is creeping up to two billion dollars of real AI adoption, and how we can achieve the lowest uplift cost and carbon intensity, and this is a true testimony that, and a call-out to our partners, that in the intelligence age, you need a partner that can accelerate AI, but more critically, adopt AI, and the kingdom stands tall as your partner of choice.

Laura, let me ask one follow-up question, and then—

It’s probably your follow-up question, so go ahead.

Let’s see how close we are on this one. Excuse me. Actually, I want to calibrate the kingdom’s ambitions here.

Tell me. At a minimum, I heard you say that the kingdom wants to AI-enable the organizations and institutions of Saudi Arabia to take better care of the people of Saudi. You want to have amazing, not just digital, but AI infrastructure for life in Saudi Arabia.

That seems to be like the least ambitious thing that I heard you say. even though that’s massively ambitious. Are your ambitions to join the global stage of tech ecosystems that are transforming the world right before our eyes?

Trust me, the first time I met His Royal Highness, even when I was in the Silicon Valley, every year he would double or triple the target on us. So the ambitions is indeed global. And His Royal Highness has an investment thesis.

The more prosperous the kingdom, the Middle East is, the more prosperous the world is. And it’s not a surprise that we fuel 50% of the digital economy in the kingdom, the region. We fuel 3x the tech force of our neighbors.

And as a result, we fuel 50% of the VC funding and the number of unicorns. And as a byproduct of that, it’s not a surprise that the World Economic Forum called out Saudi Arabia as the number one and number two digital riser consecutively. Going back to the intelligence age, we have energized the industrial world and we helped the world achieve more than $100 trillion of economic value.

We want to help the world achieve the next $100 trillion by energizing the intelligence age. And we’re laser focused, since we’re talking here about the technological walls, we’re focused on addressing the energy wall, 83 gigawatts the world needs. We have already allocated, His Royal Highness has a committee that meets monthly on this.

And he has designated one of the subcommittees, His Royal Highness Prince Abdulaziz bin Salman. And we have allocated land energy that is available with more than 10 gigawatts worth of capacity today, in which we can deploy. And we’ve already have announced it in the last visit of His Royal Highness to the Honorable President in DC.

We had Jensen Wang, we had Elon Musk, who are today in Davos, all have announced major investments and deployments with definitive agreements to go large in the kingdom. In terms of adoption. One true story, Allam, the most powerful Arabic LLM, we presented it to Adobe and Adobe right now have adopted it across all of their product suites.

If you want to use an Arabic LLM it’s powered by the Kingdom of Saudi Arabia, and we have partnered with Qualcomm to bring to the world the first hybrid AI laptop and endpoints. So these are true testimonies that the Kingdom, we’re not going local here or regional, we’re going global.

You are not playing small ball, if I use the American baseball analogy.

Israel has never played small ball.

Small ball is not a thing we’ve associated recently.

Trust me.

Laura, before you ask your question, can I bring our other two panelists? Oh, sure, sure. Vimal, I’m sorry.

No, no problem. Vimal, let me go to you. You run Honeywell, which does business at the cutting edge of technology all over the world.

As somebody leading an organization that interfaces with a lot of governments and a lot of ecosystems, could you talk about the things that you see that give you optimism, that you’re working in an ecosystem that’s heading in the right direction, versus the things that you see that give you pause, you think this might not go so well.

Is that a fair question?

Absolutely, and I think we as companies, Laura made a great point initially on ecosystems and ecosystems between the university system and the governments and how it creates innovation like Google. But companies like Honeywell and many others have very large investment in product development, and they’re thinking ahead three, five, seven years, again with a strong linkage to the universities. So one of the things we realized for last five or ten years is we need to be in the front end of interfacing with the governments to share with them what are we doing, and have ability to shape a bigger picture.

Governments like Saudi are very proactive. We have access to people like His Royal Highness and others. Very high access to share where things are going, and I’ll give one or two examples.

If you think about the world of AI, which is impacting every industry, and therefore it has impact on energy consumption, one has to think about right way all the way to the end, what will be AI used for, and is the strategy to generate more energy is for the right cause?

Because if you have a dialogue to say we need more power, we put more nuclear, we put more gas, the question I always pose is, but what are you gonna do with that? Have you been clear that are we gonna make a best video and best pictures, or are we gonna solve the healthcare problem?

Yeah, what’s your goal?

And if you’re gonna solve healthcare problem, we have solution for it, then let us solve the energy problem in different ways, is it gas, is it nuclear, is it energy storage? So I think ability to see this end to end picture, whether it’s in the government in United States or countries like Saudi or many other large economies, we see this as our responsibility, and what’s in for a company like us, if we shape the policy right, it benefits us to be ahead of the game, to understand our business model aligned with the policy, there’s something in us for that, but also it’s our responsibility as a large company to give it back to the society in other form to see that these things are critical for the success of the society, and that’s kind of where we think we have an important role to play in this whole ecosystem.

And my concern today is that while there’s a lot of dialogue on AI, it’s bigger picture implications are not being discussed in depth on what it will be used for, because if it is being used for economic prosperity, please put more power generation and do it, but it is being done for human curiosity and I’m gonna do something more interesting, probably it’s not the best use of the resources of the planet at this point of time, so how do we have that dialogue and help people understand possibility?

Are you telling me I shouldn’t be creating funny images that amuse me on nano banana because that’s ruining the planet, that hurts.

It’s using energy that might be used in other ways, is what he’s saying.

I get it, I just don’t like it, right? On that point, there is a huge amount of concern right now about the environmental footprint, specifically of AI, more broadly of the digital ecosystems, and people are worried that, again, we might like making cool pictures with LLMs, but the planet can’t tolerate that.

Is that an accurate belief?

I mean, look, the energy systems have been created over the last 100 years with the hydrocarbons. It started after World War I, so it’s 105 years. So we have to be conscious that what was created in 105 years can’t be recreated in 20 years.

Maybe we can do it in 30 years, right? So it’s always going to be a slow move to a new state. So first we have to recognize that it’s an energy mix change.

The word energy transition probably is a little wrong representation. Now, the choices we have made are limited, because if you want to scale our power generation, the only source seems to be gas, because nuclear takes 10 plus years to make. Other sources are not that interesting.

But what we have to think about in this is, how do we drive energy efficiency? AI is a good source of energy efficiency in the industrial sector. So while it’s a source of consumption, it’s also a source of efficiency.

So therefore, solving this problem holistically is a very interesting paradigm that you have to do it. But is any black and white answer known to this? I wish I had it.

I wish anybody else had it. I think the answer here lies in constant dialogue on technology evolution. Case in point is, companies like us never thought of energy storage at scale on the demand side.

Today, we feel very confident that we can do energy storage at a source like consumption of, say, hospitals, stadiums, schools. And that can take a lot of peak power off. And therefore, the energy demand is less and that is used now for AI generation for healthcare problems.

Solving this holistic issue is something we strongly believe in.

When you talked about the energy solutions available for these unbelievably energy-hungry data centers, your list was short. Your list had one thing on it, if I listened correctly. You said gas.

You didn’t say gas and renewables. Can you educate us why not?

I mean, what one has to appreciate is the intensity of energy. I always like to, I’m an engineer by background, so I always like to tell people the mix of energy doesn’t matter. How much is wind, how much is solar?

We like to advertise that. Kilojoules matter because energy intensity has to shift, not the mix. So solar power cannot produce cement.

Solar power cannot produce steel.

It cannot.

They are very energy-intensive. That’s right. They still need a gas-based heating or oil.

And even after three or five more years of innovation in renewable, not there?

It’s against physics.

Fine, absolutely.

Physics don’t allow it to do it.

Yeah, right, it’s almost as if that’s against physics.

So therefore, when you have to look at energy mix change in context of joules of energy, your challenge becomes different because the world still need to progress. World needs to build more infrastructure. It still needs steel.

It still needs cement. It still need fuels. Now, how do you do that energy mix change while you also want to build data centers and consume more energy?

That’s an interesting problem to solve. And today, the problem is single-threaded with the gas-fired power plant, maybe a little bit of nuclear. Renewables remain in the mix, but it cannot bring the amount of joules we need to produce this infrastructure which is required in the world.

Fantastic. Sassine, last but obviously not least to you, you run a chip-adjacent company. Is that a fair way to say it?

Okay, so the question on everybody’s mind about chips these days, because it feels like they’re the bottleneck for the determining factor for how. quickly things get amazing in the world. Everyone talks about the chip shortage and rationing chips and all that.

So my question to you is, you know this better than probably almost anyone else, the chip industry has benefited from this almost miraculous phenomenon called Moore’s Law since about the mid-1960s. And there are many ways to talk about that, right? One of them is that either the amount of compute you can buy for the same dollar doubles every, let’s say, 18 months, or the amount you have to pay for the same amount of power halves every 18 months.

That phenomenon, unless I’m badly misinformed, has been pretty steady, pretty consistent, and going on for something like 80 years. We’ve never seen anything like this. I hear a decent amount of conversation now that Moore’s Law is running out of steam, and it strikes me that if that’s true, then this flourishing of innovation that we have been seeing might actually slow down.

Is that a thing that we should worry about?

First, let me set the stage for our role in Moore’s Law. Synopsys is the hundred billion dollar company that nobody has heard of, and the reason for it is we’re part of an essential ecosystem. Moore’s Law does not exist in terms of continue that rhythm of 18 months of innovation without this stack of engineering innovation.

It starts at the atomic level with material selection, physics, to build a transistor, to put it on a chip. The chip has billions of devices that somehow magically they work, and now those devices, when you think of an AI chip, it’s reaching a trillion devices, and it’s being that being designed through a number of vectors that you need to optimize.

Moore’s Law is continuing, but it’s not affordable. It’s not at the same pace that what we were used to. for the last three, four decades.

Now, in any innovation, it has to be practical. Can you deliver it on time at an affordable cost? Therefore, the innovation is taking different shape.

So you start expanding at the system level to innovate. So when you think of AI, the reason it’s possible today is because of the power of silicon. If silicon is not powerful, it can achieve the performance.

You cannot run the models. The way it’s evolving is at an architectural level. You’re able to stack multiple chips in a package.

So the chips is becoming a system.

Great.

So therefore, it’s not something to worry about because Moore’s law is hitting the limits of physics. There are other aspect to innovate, which is a system level innovation.

So this is great news, if I’m hearing you correctly. Moore’s law is slowing down. That does not automatically mean that the party’s over when it comes to this innovation digital bounty that we’ve been experiencing.

Yes, there is a terminology in the industry has been referred to for the last five years or so, advanced packaging or multi-die, which is what essentially is you’re only moving the part of the chip that you must advance process technology on Moore’s law.

The rest of it is too expensive to move. So you disaggregate the chip, you break it into small chips, then you bring it back together in a system. That’s what Synopsys does.

We provide our technology to every customer that is disaggregating that system, bringing it back together. And just to give you a reference of the value in that supply chain, our company just six years ago was $10 billion in market value. We went up 10X to a hundred billion.

There’s absolutely a scaling law taking place. They keep on doing things that they could not do the week before. And I found myself in this weird position where I get up and I’m drinking my coffee, I look at the news from the tech sector, and I realized a little while back that I was no longer surprised, being astonished.

I’m like, oh, but wow, that’s a miracle. Okay, great, you know, it’s Tuesday. Is that party gonna continue for a while?

Yes, that’s the beauty of constraining a problem. Innovation comes, engineering comes to life when you constrain the problem. You look earlier, the discussion was China, US.

If you look at China, for example, they got constrained from silicon access. They did not get access to the latest chips. Then DeepSeek came about.

What happened? They could not get access to the latest technology. You start going up the stack, which is the model, you create a far more efficient model for a specific workload, and it just beautifully work.

Now, it does not mean China is further ahead than the US in models. Now, in the US, you have access to the latest silicon. And you start, what is silicon?

It sits in a data center, and that data center is used for the applications, the models, it can be for physical AI, it can be for a chatbot on your PC, for on your phone, whatever. So for each application. And there’s an economic vector, that’s where power comes in, et cetera.

And then there is a differentiation. Are you able to deliver a product that’s going to be first to market and you just cannot do it without optimizing up that stack?

If I can just add one point to that, I mean, I think the Moore’s law in terms of more part of compute is an interesting discussion. And Sassine explained very succinctly on how this is not going to end. But the bigger power is how the ecosystem uses these tools to compound the power of it.

So companies like us follow the tech world, all the innovation Google is doing or Amazon is doing and Microsoft and NVIDIA, and our engineers are able to connect the dots for the industrial sector we serve to further compound the innovation.

And I think the innovation should not be looked in the blocks of individual components. It has to be looked for the solution it provides. And the solution compounding can happen with a human brain to say, I thought this was possible, now it’s almost possible, I’m going to give it a shot and make it happen.

And I think that’s what is propelling the innovation cycle. So things which we did 20 years back were not possible 20 years back. But now we are challenging ourselves for how our systems can co-create in a different manner.

And it’s opening up a new set of economic opportunity in industrial sector. If I just make a quick point on an example, so we make building management system in a building we are sitting to make it more efficient so that it’s more energy controlled. We are doing it for 40 years.

We thought that was the best product we ever created. AI can make it even better, the energy efficiency, by another 10 to 15%. We never thought that 40 years back, but today we take that silicon, we take a compute power and put on top of it, and it’s giving that extra 10 to 15% capability, which is ingenuity of human mind, that it can solve the extra set of problems.

So Moore’s Law continues. It continues to build more and more systems so that we are able to… It’s all about economic value creation.

How do you create more economic value, whether it’s more revenue generation, more cost reduction, and that’s what companies, all the industrial companies are doing.

This is, I promise, let me say one more thing and then I’m gonna turn it over to you because I know you’ve got fantastic questions, but I have to react to this because this is the most encouraging and optimistic thing I have heard at Davos, certainly this year.

Maybe in my time coming here, this is profoundly optimistic because what you two are educating us about is that there’s been this party going on with digital innovation. It doesn’t solve all the world’s problems, but it’s a really good thing to have. And you two have just given us a very short masterclass, the conclusion of which is that that party is going to keep going, even if, Sassine, as you say, if we run into ceilings or we start to approach a constraint, that’s the wrong thing to concentrate on.

The innovation ecosystem has the tools and the incentives to keep the party going, and we should expect a lot more digital innovation. All right, Laura, I’m sorry, you had a question.

I really wanna go then to keep the party going for what? I mean, you actually first said, what should the goal be? I really do worry a lot about the fact that right now, the hyperscalers, all of them are in California, I think they’re all, they’re in a race with one another.

They’re in a race with one another to get to AGI. They’re not even sure why. They just think if they get there first, AGI would basically be able to solve all human problems better than humans.

Sounds absolutely fabulous. Why would you not wanna do that? They are financed by a whole bunch of, their financial structures really are very much return that the return is returned to investors.

It’s value creation. That’s what it is, okay? And it’s not at all clear.

There are lots of people who sort of do the numbers, look at the assumption about how much they’re going to have to sell around the world to create the value to support the financing they have raised. There’s not clear. There’s a lot of risk here.

So this is not an industrial strategy. This is a strategy of five firms competing against one another to achieve AGI. If you go to OpenSeek, which said, OK, we can’t get these chips, but actually what we’re going to do is we’re going to provide open source.

And basically then the rest of the Chinese economy can actually access this technology to apply it to their sector, to apply it to their consumers. And at the end of the day, that seems like a much more understandable approach. So I will then say I have a question for Saudis.

I keep on feeling you’re China-leaning a little bit, Laura, I’ve got to be honest.

I’m not China-leaning. I am raising questions about the strategies being pursued by the hyperscalers, all of whom are here representing AI to the world. OK?

That’s what I’m saying.

It’s actually Saudi-leaning, because it’s about acceleration and adoption coming together. It’s about acceleration and adoption coming together. You’re saying without the use cases, we can’t just focus on the supply side of the world.

We can’t.

It has to be the supply and the demand coming together.

It’s the demand. Where is the demand coming?

To save lives.

Yeah, to save lives, to actually improve energy efficiency over time because of the issue of the climate, which we can’t mention here this year, but actually I think we should. We have real constraints on us from the climate. We have the issue of youth and employment.

Indeed. Youth and employment. So you said talent development has been very important in Saudi Arabia, but you have to find ways to keep those people moving in careers that generate living standards over time that are acceptable.

That’s a goal.

So Laura, to your point.

That’s an industrial strategy goal. It’s not a goal of open AI. I like open AI’s technology a lot.

But it’s not open AI’s goal. It’s value creation.

Before you jump in, before you jump in, I just want to flag to our live participants here with us in the room, we’re going to open this up for questions in just a little bit. But this is so spicy that I don’t want to stop it right now. So over to you.

So to build on Laura’s point, I think where AI needs to emphasize is augmentation of skills. Because if you look at the broader picture, human population is generally not growing in majority of the world today. There are exceptions.

But there’s a population shrinkage in most of the mature world, including China now. So if I fast forward 15 years from now, if there are not going to be enough skilled people, and people are not willing to do work where you have to work with hand to run an operation, run a building, run a plant, run a warehouse, how that work will get produced?

And will it stop the economic progression? Or will the tools get created where one human can work of two humans? Or a less experienced person can use a tool to do a work of more experienced person?

We are focused to use and deploy AI in that context. We are more around augmentation strategy of human to make them more productive. But that creates economic value.

And that can create jobs.

This is fascinating. Because I’m hearing two problems articulated. They’re basically the mirror image, or no, no, the plain opposite of each other.

Laura, I heard you talk about the fact that there might not be enough jobs to go around, that we’re creating some conditions for technological unemployment. I heard you just identify the exact opposite concern. There might not be enough people to do all the work that need to be done.

Which is it?

So you have to differentiate between a work getting automated and augmentation.

That’s right.

Because a human divides a work into three buckets. You define the problem. You execute the problem.

And then you check. This is how humans have evolved over the last 1,000 years. In industrial world, still humans have to define what problem to solve.

You can automate to execution, software can come in, but the first and third step is augmentation. Let’s take an example. Can AI read an X-ray?

Yes, but will you conclude a result of AI to say, I read your X-ray and here’s a treatment. You don’t want a doctor at the last step to say, please tell me, is it the right one or wrong one, right? And that’s where the three-step approach has to be done.

So it’s augmentation in the skills, which are critical for the planner. So I think if the focus is towards augmentation, economic value creation will be higher and job losses will be lower. But if the focus is on the code automation and others.

I couldn’t agree more. It’s all about acceleration adoption with the augmentation approach. Just to build on what has been said, there are a few players that are just focused on the supply side of the world.

That’s like throwing good money after bad. And that’s why it’s not only takes capital, but a captive market and real use cases. So the X-ray example, we have the largest virtual hospital today in the world, part of the success story that we have in the year 2030.

And what has happened as we deployed those AI agents, for those radiologists to be able to detect whether a tumor is benign or malignant, they were able to see more CT scans, more MRIs, more X-rays to be able to serve and help and protect more lives.

Taking a step back to that first robotic story of a heart transplant, he’s able to get patients outside of the ICU room and the CCU room within four hours, or 48 hours versus four to eight weeks. This is a remarkable example of how, if you’re talking about a responsible approach of leadership in the intelligence age, you need that acceleration adoption with the augmentation approach.

While I agree, there hasn’t been enough thinking of how to transform education and the talent that will be replaced with intelligence. There is no question about it. Today, if you’re graduating in computer science, you don’t have a job.

Very difficult. Five, six, seven years ago, you could not get enough of them.

Enough jobs.

And so there are tasks, if you’re able to move it to automation, you don’t need them anymore.

You don’t need it.

As a company, I have 30,000 employees and about 25,000 of them are engineers. And those are the most sophisticated engineers in the world.

Many part of my workforce, I’m flattening it.

Why? Because I’m forcing and pushing to drive more augmentation, all the stuff that’s been said. But what does that mean for the early in their career?

Coming in.

They don’t have a job. And those are statistics there across the world that the unemployment for areas that AI is able to automate is being impacted. Now, the counter to it, well, that’s great.

You can do more innovation. But, okay, that’s easy said. But innovate to build what?

There’s going to be a period of time where there’s going to be a stress in the economy due to AI. But all of that being said, I’m a huge believer that you need to run a race with it. Because it’s so significantly disruptive.

So hold on. There will be bumps in the road, but we still have to accelerate.

You have no other choice.

You have no choice.

No, you could try to mandate that you’ve got to slow down. Governments have tried to do that before.

But then you’re missing a huge opportunity from solving significant problems. We may cure cancer in our lifetime because of the technology we have.

Helped us focus on the right areas.

I think helped us focus on the right areas, I was thinking about all of those engineers and basically I was thinking okay if computer science PhDs can’t get jobs as fast, one of the things you could imagine is you could imagine more support for the universities so those computer science, brilliant engineers could stay and continue to work on innovation in basic science and sooner or later they would actually develop a product or a service which they could then go into the marketplace.

I actually think your argument is to put in more basic science research so you can support these people for longer periods of time as postdocs because you can’t say oh well just go out into the world and become an entrepreneur I mean that’s really you don’t have anything to do that.

You don’t have the ability to do that.

We’ve got time, if everybody is concise, we’ve got time for I believe one question from the audience. Sir the only rule, I’m sorry, is threefold. It has to be concise, it has to be clear, and it has to be a question.

Quick question, 10 years from now, you’re on the same panel, what is your prediction now that the world will be?

Oh yeah, okay, beautiful. Lightning round to end with, we’re 10 years in the future, what’s the big story of the previous 10 years? Can you start?

History is a great predictor of the future.

We’ve got to go quick, it’s got to be a lightning round.

Lightning round, for every dollar made in infra, you’ll see 20 bucks in software, you’ll see more use cases and more proliferation of these technologies to help the people, planet, and prosperity.

Laura, short quick prediction, 10 years.

I think I’m very concerned about the national security breaches of all of this. I think we could have some serious issues that involve the geo-economics that we’re not.

Pervasive use of physical intelligence that will dramatically change and improve human lives. I can hardly think of a better note to end on than improving human lives.

That’s a good one. I think that’s great. Let’s do that.

Thank you all my panelists, this has been great. Thank you for joining us. Let’s do that.

Thank you.