Leading AI nations are racing to preserve dominance while new contenders rise and others struggle to break dependence on foreign capabilities.
As alliances reshape the balance of power, how is AI redefining the path to economic growth and global influence?
At Davos 2026, panelists framed AI as a geopolitical and economic accelerant, but warned its benefits will be uneven without deliberate diffusion. IMF Managing Director Kristalina Georgieva described an “accordion of opportunities,” ranking countries by infrastructure, skills, diffusion, and governance. She estimated AI will “touch” roughly 40% of jobs globally, creating gains for some while “squeez[ing]” middle workers and making entry-level pathways harder. Microsoft’s Brad Smith argued the U.S.–China race is about both frontier innovation and worldwide adoption, while reminding audiences that transatlantic tech capacity and capital ties remain decisive. India’s Ashwini Vaishnaw rejected the notion that only frontier models confer power: “ROI doesn’t come from creating a very large model,” emphasizing practical deployment and a government-backed “common compute facility” of 38,000 GPUs to broaden access. Saudi investment minister Khalid Al-Falih stressed optionality and commoditization: AI “will quickly be commoditized,” so countries must invest across the stack while protecting values and reducing bias through sovereign models. Governance priorities converged on skills, infrastructure for the Global South, and “techno-legal” regulation to tackle deepfakes, bias, and resilience against “weaponization” of platforms.
And hello everybody. I am Ian Bremmer, president of Eurasia Group and this is AI Powerplay. I did not come up with the name for this panel. You will be very pleased to hear. We have a lot to talk about. I'm going to very briefly introduce the very distinguished panel of guests. Immediately to my left, the managing director of the International Monetary Fund, Kristalina Georgieva. Brad Smith, the president and vice chair of Microsoft. Khalid Al-falih, the minister of investment of the Kingdom of Saudi Arabia. And last but certainly not least, Ashwini Vaishnaw, the Minister for economic, Electronics and Information Technology of India. So a pretty good global breakdown. Interest, responsibilities. We're going to try to get to a couple of questions at the end. If you have something really smart to say as we get towards the end, try to make eye contact. We'll see what happens. So I want to start off with Kristalina, and we're going to begin with sort of the geography, the geopolitics of what's happening in AI right now. I mean, you'd think it's all about Greenland at Davos this year, but actually there's another Davos going on which is very fast moving. It involves an incredible amount of investment. It's one of the reasons why you just upgraded the economic outlook. Talk about from your your your global perspective. How is power changing around the world with AI.
Oh definitely it is. When we look around the world and we see what is injecting resilience and strength in the world economy. AI definitely is a factor. And so is the advancement of private activity. Over the last decades, the state moving out of the economy, letting private private business do its part. And those two things work extremely well. So we created a index of preparedness to see how well are different countries ready for AI. I would put them in three categories. Those who make it happen, those who watch it happen, and those who are saying, what the heck is happening. And actually, on a serious note, we look at four things. We look at physical infrastructure. We look at labor skills, capabilities. We look at diffusion. AI may be happening, but if it is not changing the economy, it's not so relevant. And then we look at regulation and ethics and then we rank countries. Not surprisingly, we have at the top a very small group of countries. Now in the current environment, probably would be interesting to recognize that the United States, Denmark and Singapore are the top three. And of course, China is with a very potent capabilities. But China is so big that you can't get that high in this ranking. Not surprisingly, we have many emerging market economies with comparative strengths. Saudi Arabia would be one of one of them. Actually, India would be one of them because of the bet on it that India is making that are in the in the higher spectrum, but low income countries and a very big number of mid-sized middle income countries are way, way behind and they're behind on all four. So the world as a whole is already experiencing the arrival of AI. But I do worry about the accordion of opportunities that are much more present in some places than in others. And then we look at the impact on labor market. It is quite dramatic. We calculate that on average, 40% of jobs are touched by AI, either enhanced or scrapped, or changed quite significantly without implications for for better pay. In advanced economies. This is 60%. In low income countries, 2,526%. Again, accordion of impact. Now my main message here is the following. This is a tsunami hitting the labor market. And even in the best prepared countries, I don't think we are prepared enough. And if you allow me to add one point.
It's just going to take away from your time later. Kristalina. But that's okay.
I know, I know, I know you, you you are like an accountant. You you hold you hold this to account, and I'll give you two minutes from the next one.
Okay.
So what I want to say is that we did something very interesting. We said, okay, how much are actually jobs changing, really? And what we found out that in advanced economies in the United States, for example, you read advertisements and 1 in 10 would have a new skill that didn't exist before. At least one new skill, maybe two, maybe three, maybe four. And then these guys would get get better pay. So what is the impact? The impact is they have more money in their pockets. They go to restaurants more to movies more. So demand for low skilled labor in services goes up. And in fact, we squeezed this poor guys in the middle in the jobs that are not enhanced or, imposed more. And the other category of people really, really affected young people who go for their first job. So, so.
Power is changing.
I owe you I owe you one.
Minute.
And 26.
Future panels. I'm taking this off as well. So many, many issues of both power distribution inside countries, which I hope we'll get to. But first, around the world and those three categories that you remind everybody at the beginning, you make it, you watch it being made or you have no idea what's being made. The countries in those categories don't necessarily always align very well. First category we've got the US and China, very little cooperation, virtually none on this issue, arguably decoupling second group, a lot of movement. And as we're seeing this week, a lot of concerns about the nature of like the transatlantic relationship, how that plays out on AI and technology. Very important. Brad, talk us through the implications of this.
Well, certainly you see the US and China competing on two very important levels. One is the leading edge of innovation. Who is making the best chips, who is producing the best models. But the second aspect of competition is really diffusion or adoption. As you know, each country and the companies from each country are working to spread their technology around the world. I think it's easy to forget, in a more global economy, just how important the transatlantic ties are. When you have a conversation on a week like this about an island like Greenland, of course it's a national security topic, but it needs to be considered, I think, in the context of these economic ties, when it comes to AI, I think people in Europe often look at the United States and say, well, we need this or we need that, but they forget they have ASML, they have Ericsson, they have Nokia, they have SAP, they have Siemens. There is a very important tech sector in Europe already. And if you look at the ties across the Atlantic, it's easy for Americans to forget that 70% of foreign investment into the United States comes from the rest of NATO. 40% of American exports globally go to the rest of NATO. So we always need to remember the context in which these issues need to be considered.
If you think about the changes that AI is having on the geopolitical environment, Brad, would you say that that that AI is doing more to bring countries together? Is it doing more to force countries apart, or is it on average kind of absent from that conversation?
I would probably say on average it remains absent, but it is going to become more important every year. And when you look at the kingdom of Saudi Arabia, when you look at India, I think you see the future and you see the role that AI is playing there already, and you see the role that that will play, I think, in both growing their economies, but connecting their economies in new ways with the rest of the world.
So Ashwini, incredible talent base, fastest growing major economy in the world, an AI player. But clearly in the second grouping that Kristalina is talking about, have to think about alignments with the United States or China to a degree. But how much do you have to think about that as a country like India, how much can you chart your own course irrespective of what the Americans and Chinese are doing?
Actually, clearly in the first group. And the reason for that is there are five layers in the AI architecture the application layer, the model layer, the chip layer, the infra layer and the energy layer. We are working on all the five layers, making very good progress in all the five layers on the application layer. We will probably be the biggest supplier of services to the world. Go to an enterprise, understand the business of enterprise, understand the working of that enterprise and provide that service using AI applications. That's going to be the biggest factor of success or successful deployment of AI, because that's where ROI comes from. ROI doesn't come from creating a very large model. 95% of the work can happen with models which are 20 billion or 50 billion parameters. We are creating a bouquet of such models we already have. We already have a bouquet of such models, which are now being deployed in multiple sectors to increase the productivity, to increase the efficiency, to increase the effective use of technology. So our focus is very much on making sure that AI diffusion happens in a very big way. And I do not know what the IMF criteria has been. But Stanford places India as third in terms of AI penetration, in terms of AI preparedness and in terms of AI talent. All the three are actually on AI. Talented is number two. So I don't think your classification in the second book is right. It's actually in the first.
So talk about in India, in an environment where the, the, the AI shifts in geopolitics are happening so quickly. Again, this was a conversation that didn't even exist at the World Economic Forum five years ago. And you now have radically different capabilities in different countries around the world. India has become a geopolitical player in its own right in the last ten years. Didn't even want to play geopolitics before Modi came in. How does AI play into that capacity around the world, and to what India wants to be on the global stage?
Listen, if you look at the way AI is shaping geopolitics, what can a country which has a very large model, let us say, without taking any names, can it switch off that model? Fair. Switch it off. What will happen to a country like India? We have our own bouquet of models, which can be used for 95% of the work that we require to do. So does does creating a large model give you a geopolitical power? I don't think so. It might actually be causing certain conditions where the people who are creating those large models might go bust in the coming years. You never know, they might go bankrupt in the coming years. The situation is we have to understand the economics of this new, I call it fifth Industrial revolution. We must see the economics of the fifth Industrial Revolution. The economics of this fifth industrial revolution is going to come from ROI. ROI is going to come from deploying the lowest cost solution to get the highest possible return. If you have a 50 billion parameter model, you can deploy it using one GPU. And if you have a 30 billion parameter model, which is absolutely good for 80% of your work, you don't even require a GPU. Where is the geopolitical thing in that? You have a large number of CPUs working in the entire world, and people are coming with custom silicon from amazing number of companies and countries where you wouldn't require to be dependent on any particular country. So that the so-called geopolitical edge that you are probably hinting at is not there.
So given that, I mean, without naming names, Ashwini was just talking about, you know, a lot of people that are have been raising a lot of money in the United States with models that he thinks aren't going to be as effective as India's model. Whatever bucket they're in now, you're the one that's thinking about deploying enormous amounts of assets for your country, both in Saudi Arabia and all over the world. And as you're thinking about the most revolutionary set of technologies out there, which what are you looking for that's going to make you convinced that this is a winner? This is a loser, as these different countries and different companies are doing very different things.
Yeah. Well, first, let's I think everybody agrees that AI as a general purpose technology is truly the transformation of this century and of our time. However, like transformation before, I think it will quickly, quickly be commoditized and it's not going to be held in any one company or any one country. The race is on. Everybody wants to build the infrastructure for it, but it is the, I think, the essence of AI's power is it has to be accessible. So the words diffusion is not just within economies that have to compete, but I believe it has to be done globally. From our perspective as an energy producing nation, the diffusion of hydrocarbon energy that Saudi Arabia produced for nine decades has enabled tremendous, tremendous, human development in countries like India, China, United States, Europe, where that energy transformed economies and people's lives. The internet did the same thing. There were a few companies. Microsoft was one of them that had a lead, but ultimately it's coming from across the world, including emerging economies and developing nations. We are manufacturing servers for data centers today in Saudi Arabia through partnerships. So we believe we believe that optionality is very important. We don't know. We don't know who's going to be ahead for five years from now. I think it's clear US companies that have, broke out of this, technology race, are ahead today. But our the essence of Saudi Arabia's strategy towards AI, it's a huge boost for diversification. Vision 2030, launched by His Royal Highness the Crown Prince almost ten years ago, was underpinned by diversification, using new economies, new economies. So the energy transition, although it may appear to be competing with our traditional resource of hydrocarbon energy, is actually a pillar of our diversification. We're going to to be 50% renewables in our electricity mix and that renewable will power will power AI. That is going to be a global commodity that we will that we will work with. And just like India, we know this is not just about infrastructure, data center and the energy competitive advantage that we believe Saudi Arabia is second to none. We're investing across the technology stack in applications, and llms, and in connectivity, again, because we believe that this is going to be a global good. So just as important as building the data hub that Saudi Arabia is building, we need to be connected. And we are connected to Europe, Asia, countries like India, China and Japan because we want that data and that that AI power to be transmitted across borders and across, across economies.
Now, as we think about AI as having dual use capabilities, as the United States government is leaning more into industrial policy with other countries around the world, as the Chinese also have a lot of leverage, in the investments that they make and that they accept. Are you feeling any geopolitical pressure in the decisions that you make from an investment perspective into these areas?
You know, quite frankly, we have invested across across the globe and we have invested in Saudi Arabia with companies from East and West. US is huge today because of their technology lead, as I mentioned. But we've also had investments with Chinese companies in China and digital technologies. We've invested with Japanese companies, Korean companies, across the technology sectors that we invest in. So optionality is very important. It's something we have now and we protect because we, we, we believe that we are the owners of our own destiny, and we will not let go of that.
So if that's the broad geopolitics that we're looking at, Kristalina, you brought up at the beginning, also inside countries, lots of people that are not necessarily benefiting. You're already seeing improvements in economic numbers from productivity and AI. You're already seeing that.
What we are seeing is that, there are indeed jobs that get enhanced. And we also see jobs that are replaced by AI. This is happening categorically. It is hard to have a consolidated and broadly accepted definition of how we measure the way we measure. At the IMF, we have a fairly big range of impact on growth, global growth from 0.1 to 0.8%. Let me just say that 0.8% is huge. If we get 0.8% boost on productivity, this would make global growth now higher than in the pre-pandemic period. 0.1 is kind of modest. And then the question is, how do we know where we land? And what we are doing is we are working with other researchers to try to capture productivity enhancement. And I can tell you it is not easy because is it because of AI, or is it because, organizationally, there are improvements that are made? I'll tell you, in my organization, the most visible places where AI is boosting productivity are two one translation and interpretation. We got from 200 to 50, 150 are replaced by AI. And in research analysts where we are actually just able to do much more high quality research. In other words, it is enhancement, not a replacement. My big worry is that you go in communities where AI is not present and there how do people prepare for it? There is nothing happening now. And actually, we did something. I'm not going to vouch 100%. This is correct, but we did a review to see countries where there is demand for AI skills, whether this demand is matched with supply of AI skills. And we found very interesting picture. In some countries demand is very high, supply is low. Some actually are developed countries. In some countries supply is very high. You have tons of skilled people, but the economy is not absorbing that supply. And the sad story is the countries where there is neither demand or supply. And that risk of this massive divergence is at the country level, then mirrors within within a country.
So so Brad Kristalina, with this, you know, evocative, accordion analogy which is affecting not only countries but also populations. You've been on the front lines of this in the United States. You see. Now, suddenly this raise in opposition to data centers and people saying, oh, we're unhappy. You know, we don't think the water, it's electricity, we're not going to see the jobs. I mean, and a lot of people expect that given the the shift in skills that are necessary, given the transition, that you're going to see, that America is ripe for another wave of populism. How how do you think the companies, not just Microsoft, but across the board, need to get ahead of this? What do they need to do that they're not necessarily doing now?
Well, the big issue in the United States is, as you've just mentioned, it really is around communities with data centers. And yeah, it's coming at a time when the number one political issue, the number one economic issue is probably affordability, the impact of inflation. So people see these large construction projects. They know that those jobs actually are good jobs, skilled labor jobs, not just, you know, people doing construction work, but it's skilled electricians, skilled pipefitters. But they also know that once the construction is over, the number of jobs is still significant in the hundreds, but not higher. But what they're really asking is, what does this mean for me in my family? Are we going to pay higher electricity prices? Is the water pressure in our showers going to be impacted? Who's really going to get these jobs? Is it going to be my family and my neighbors, or is it going to be somebody who moves into town from somewhere else? Those are completely legitimate questions, and I think it's incumbent on all of us in the industry in the United States to address them head on and offer the kinds of assurances that people need that we will invest in electricity so that people's electricity rates don't increase, that we'll replenish more water in these communities than we use. That will work with the kind of training, whether it's skilled labor or IT jobs or other ongoing jobs, so that local residents can fill them. And I think as data centers spread, inevitably people in other parts of the world will ask the same question if people benefit, will it be us? And I think people have a right to expect their share of the benefits.
And to be fair, I want to repeat this. You would would say that today a much bigger issue for the tech companies in AI is response to these concerns about data centers and affordability than concerns about job loss or job transferability. In terms of right now.
In terms of the politics of 2026, for sure. I mean, the world is sort of a quilt, if you will, with different colors of fabric. When you look at the construction of data centers in the US, local communities block $98 billion of private sector investment in just the third quarter of last year. You come to Europe and governments want to spend taxpayer dollars to subsidize data center construction. You look at the Middle East and there's obviously a major economic strategy of creating an export, you know, a token exports or exports, if you will, out of, say, Saudi Arabia, the UAE and the like. China probably has an ability to go faster in some ways when it comes to bringing electricity online and getting infrastructure built. You go to Africa. Wow. We just need we're still.
There isn't electricity.
We need more electricity, and we need more data centers.
So, Ashwini, when you think about, how AI can be used, I mean, technology. India already did an incredible job with the Aadhaar. Suddenly you're able to bring public services to people, and you're improving growth, and you're improving their per capita income without actually blowing out the budget. What can AI do? How are you deploying AI to further that message? How fast are we going to see it? Where are we going to see it?
Absolutely. Every sphere of life and economy we are focusing on diffusion, diffusion of AI and in a very systematic way. So okay, what is the biggest constraint? The biggest constraint is availability of GPUs. How do you solve that constraint? To solve that constraint, we decided to have a public private partnership in which we empaneled 38,000 GPUs, which are a common compute facility available to the entire population. Unlike in many rich countries, where the big tech basically controls the access to GPU, we decided to create a public private partnership in which the Common Compute Facility is enabled by the government and subsidized by the government, so that entire population, all the students, researchers, startups, they all get access to it. And the cost is practically one third of the cost in most other countries, that is first. Second, having a set of free, a bouquet of models which basically meet most of your needs. Third, making sure that people understand this technology, learn this new technology. Already, we are going through a program for 10 million people to be trained on AI skills, for making sure that the IT industry, which is a very significant industry in our country, pivots in a very systematic way towards providing services to Indian companies as well as to the global, companies using AI as a very effective enabler of efficiency enabler, a multiplier of productivity in any operation that they do. So that's a very systematic way we are moving.
Thank you. So, Holly, I want to ask you to look inside the country. Last time I asked you to look outside on winners and losers. The funny, the crazy thing about Saudi Arabia is that you're kind of starting from scratch, right? I mean, ten years ago, you'd go to Saudi Arabia, and I mean diversification. They'd talk to you about petrochem. And today, like the economy is suddenly truly becoming diverse. It's healthcare and it's tourism. It's ten years ago, you barely had women in the workplace. And today, like, it's an astonishing involvement in every part of society. So given that like, where are the AI is kind of hitting your economy almost from scratch as a diversified and integrated society with, with what, 30 million people, whatever it is, how is how is how are you deploying AI with people who are looking completely differently at the world today?
Well, first of all, I would disagree with coming from scratch. You'll be surprised how tech savvy, tech native the Saudi population is. 70% of the Saudi population are below the age of 35, and the majority of them are as comfortable with digital technologies as any other country, in the world in terms of policy and regulation. When vision 2030 was launched by His Royal Highness the Crown Prince, we identified technology as the key enabler. AI included, and started building the policy, the regulation, the platforms within the country, the data centers for the sovereign, data sovereignty that that was key for portions of the data. But in addition to data privacy, we had an open data. We talked about diffusion and access to compute, but access to data to achieve the same purpose of research, drug discovery, productivity improvement, having a policy also of open access to data was a pillar that was launched before Covid. This is back in 2018 and 19. We have a ministry level organization called Sada, Saudi Arabia, the Saudi AI and data authority that regulates and sets the guidelines with flexibility to allow the evolution, of AI to take place, and the innovation to take place. But it also protects and regulates and makes sure ethical standards within the Unesco. Saudi Arabia was one of the first countries that proposed guidelines for the country on on ethics in AI. Then we create a national champion, which is co-invested by the PIF or sovereign wealth fund and Aramco that is investing at scale, way beyond the need of Saudi Arabia and the Middle East. Because as I mentioned in my first question, we think we think AI is going to be a very key pillar of the global economy, and it's going to be globally traded and therefore connectivity. And we are playing to our strengths, but we are also quickly bridging the gaps that, we, we recognize we have. So we're developing our own LLM Saadiah developed the first Arabic large model called Alam. And now it's owned by Humayun, which is our national champion, and they're building on it. We have applications, I can tell you many, many use cases where over the last few years we have deployed, we have deployed, AI applications in healthcare. It has cut the time to diagnose diabetic eye disease by 80%. And the rate of, and the thousands of man hours of clinical physician hours have been saved. In that case, we have our, we have our renewable energy company, Acwa power. They have cameras, on the blades of their winds that identify birds approaching from from far away. And if they think they're coming near the windmill, they shut.
You got to tell President Trump about this.
They shut him. Okay? They the same company have reduced their chemicals in water desalination by 30% using AI. And the use cases are abundant. So we're not starting from scratch. Going back to Kristalina, we're in your first category.
I, I have not declared either India or Saudi Arabia in the second category. So I stand to, accept your claim.
Thank you. Everyone is in the first category. We have participation prizes.
There's no.
I'm not going to go that.
Far to jump in.
I think we should let's not talk about Saudi Arabia or India for a moment, but let's just talk about the global North as a whole and the global South as a whole. You know, the diffusion report that we released a couple of weeks ago estimated that today, generative AI is used by 25% of the population in the global North, but only 14% in the global South. And the gap is getting wider. So if you zoom out and you say, what does this mean for the future of the world? I'd put it in the context of infrastructure and the history of infrastructure. Why is the world so divided economically? Well, I'd say a large part of it is because during the entire colonial era, the colonial powers invested in building railroads in places like India and across Africa. They were important to move troops, to control territory, to extract minerals. But they never built power plants for the population. Well, AI exacerbate this divide. Or will it close it? It's only going to close it if we embark on building infrastructure across the global South. And we need strategies that stimulate demand, that furnish supply. India, Saudi Arabia, they're on the right track. It's hard to look at Africa as a whole and be equally optimistic, and we need to think about that as well.
So as we move into the last segment and if any question or two raise your hand, I will try. I see a couple. Okay. We'll try to get there. I want to talk a little bit about the, the governance environment. And you just mentioned, you know, a big problem which is absent international governance, trying to figure out how you're going to build this infrastructure. I mean, you know, in this environment, it's hard to say that the Americans are more committed to that than they have been the last five, ten years. China has been pretty inward looking in many ways, the last five, ten years. Those are some big challenges. This space is moving a lot faster than governance capabilities. So if you could wave your magic wand over the next few years with most of the leaders that we presently have now, what are 1 or 2 things that you think are feasible that would actually improve governance, that would make a positive difference in addressing both the challenge that you just raised, but also some of the others that we've been talking about the last 30 minutes.
Well, the first thing I would say is look back at the skilling topic, because it's a lot cheaper for governments to invest in skilling than it is, frankly, to invest in data centers. But if you invest in skilling, you start to stimulate demand for the private sector to invest in data centers. You can skill government employees. That has proven to be a very effective strategy for kickstarting demand. You can, you know, skilled data scientists, you can do that through universities. That's where you start to get people who can then build the local applications. And I just think it is a critical element that is not getting the attention it deserves.
Khalid, what is the piece of governance or regulation that if you saw it in a country around AI, you would say, this will make me materially more interested in investing in IT.
And governance.
Yes.
Well, you know, I generally I think the concern we have with AI is, is biases in the data sets that the models have been learning from. So, someone who's coming from Saudi Arabia and the Middle East, it's important for us to also build our own sovereign models and to make sure that unbiased data is fed and taught to the models so that they are fit for purpose for us. They need to be consistent with our values, and our value sets have to be protected, because AI, as we gain all of the efficiency and productivity and competitiveness that we inevitably will gain, we also don't want to lose our value and our character. And that, I think, is an issue of global governance, where we have to recognize that these these models and these applications cannot be developed in one country, say, Europe, US, China, whatever it is, and then assume to be relevant and applicable to every other country.
Okay. Last comment before I go to a couple of questions. Ashwini, I wanted to say, I know that you and the way you think about regulation and governance in India are not just thinking about the laws that you're creating, but also how you use the technology to actually create and implement. I'm wondering if you could share just a moment on that with the audience.
Absolutely. Right. In case of, technologies like AI, it's very important to have a techno legal approach to regulation. It cannot be just a law that you pass and believe that everything will fall in place. You have to create technical tools and technologies to counter the, harmful effects of, for example, bias, as Khalid said, for example, detecting deepfakes with a accuracy which can be taken to a court and be properly, judicially, checked. So those kind of things you require techno legal approach. We are following techno legal approach creating solutions which mitigate bias, which help in detecting deepfakes, which make sure that unlearning can be done properly before you deploy a, model in an enterprise. So those kind of technologies we are developing.
Thank you. So I'm going to try to take one question to begin. Please recognize yourself. If you can be quick. I'll try to get to two. We'll see where we get.
So I've been asked to stand up, so I shall, I'm Pranjal Sharma, I'm a columnist, from from India. And I focus on the intersection of tech and policy. The key word to use is weaponization. We've seen weaponization of digital platforms and AI. We saw a case in India where a company's digital footprint was switched off. Within seconds. We saw two justices of the International Court of Justice faced the same. So my question to all of you is how critical is this threat of weaponization of digital platforms, including AI? And is that therefore driving this piece of tech and AI sovereignty beyond just the data sets and controlling data?
Rather, it feels like it's most for you?
Well, you know, every technology is both a tool and a weapon. There's a book with that title. And I think the unfortunately, just as there's almost an infinite way, number of ways to turn AI into a tool, you know, it can also be turned into a weapon. I would highlight two issues that I think are really paramount today. One is the use of AI to increase cyber threats. And that just is a classic case of where you need a united response from both the tech sector and governments working together. So in part, we're using AI as a cyber shield, if you will. But then the other issue, and the one you're really pointing to is in a world where people are so dependent on technology, when governments, when countries are run on technology, is there a risk that technology gets turned off? And I think we have to continue to advance the kind of international dialogue. So we have agreements between countries that will take that off the table, if you will, that will not make that part of a trade debate. If people want to apply tariffs, well, you're increasing the prices, but the goods are still available. And I think we need the kinds of steps, as we've been pursuing, say, with a country like India, for example, to provide assurance of supply. And I think this also really naturally involves more local control, local laws, local suppliers, local partnerships. All of these things have become part of a complex web that are just indispensable for how this technology is used in the future.
Urgency of lack of international engagement on that last one right now. Scale of 1 to 10.
Yeah, we're I'll glass is half full. It's half empty. It's a five Ian. It's there's there's so much more that could be done.
Question.
Namaskar. Hi. I'm Ishaan Pratap Singh from the global Shapers community, the New Delhi hub. I'm a 22 year old entrepreneur. My question is for Mr. Smith as well. And what would be the correct analogy for the example you used about, railroads and power plants in context of AI? And do you think the solution to fix that is to, put universities and centers at the forefront rather than, companies doing the job?
The thing that I would highlight is that we're what I would suggest in the seventh wave of technology driving infrastructure, we've gone from canals to railroads to electricity to the telephone to highways for cars and airports for planes. Now we have AI. It requires infrastructure. I think the unlike, say, airports and highways. But like the first for the private sector is investing globally. That is good news because that is helping to spread infrastructure around the world. But there are key shortages we need to address. Probably the most important in most countries is for people. But Kristalina was saying India actually is providing much of the IQ that is creating IP for the world. But if you look at Africa, for every one data scientist, there's 14 data scientists in Europe. That is a shortage that governments and universities can help meet. I would also say then we need more capital to be deployed where the market is not building these data centers, development banks, development assistance can play a role, but governments can help stimulate demand. When the public sector adopts AI. When countries consolidate demand by putting together, say, regional agreements to make enable a data center to serve six countries and not one that will stimulate more investment, we need to get the investment moving, and I think governments are best served when they survey the market, look for the market failures and fill in the gaps.
Last quick question a young woman in the front.
Hello, I'm Maria from Portugal, also a global shaper. I'm an AI developer working on drug discovery. So you've mentioned the problem on entry level jobs, but you also mentioned education and has a follow up question. Yes, education is very important, but the people are leaving universities and they need the entry level jobs. I don't know if any of you have some thoughts on this question of yes, we get education, but then how can the youth actually get this entry level jobs? And what solutions can we actually bring for this?
Kristalina.
Well, the one important thing we see is to recognize that how people are prepared has to leave space to be ready for new skills and be able to fill applications where these new skills are a requirement. In other words, learn to learn and adapt rather than learn specific technical skills and stop there. It is not an easy, problem. And this is where we are telling governments that they have to invest much more thinking into helping communities, individuals, businesses to be prepared for the world of AI. Because it is here. It's no more a world of the future. And I want to say one thing about Africa. I have a very deep conviction that the way we can help Africa is if we finally fulfill one commitment that was made that is not very expensive, $15 billion to get every African citizen, business and state institution connected to the internet. It is a step that would help tremendously. Of course there are issues of electricity. They also need to be resolved, but it is not unresolvable if there is will. And there is this, strength of helping countries not to fall so dramatically behind. In my institution, we focus a lot on Africa. We do one thing which is digitalize all government services. It serves as an impetus to get countries.
Moving. And actually we strongly advocate for this issue of skills. Be very proactive. Don't allow this to come so ahead. Than than young people are on the street and desperate.
I'm glad we ended with that. It's a good note. And please join me in thanking our panel today.
Thank you.