The global AI divide

Summary

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Business Daily – "The Global AI Divide"

Podcast: Business Daily (BBC World Service)
Episode Date: September 15, 2025
Host: Hannah Mullane

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Episode Overview

This episode explores the growing global divide in artificial intelligence (AI) infrastructure, investment, and influence between the world’s two dominant players—the United States and China—and the rest of the world. Host Hannah Mullane discusses the various economic, technical, and political barriers lesser-resourced countries face, highlighting real-world voices from Argentina, Kenya, and Europe. The episode examines how countries and companies are forced to adapt, innovate, and strategize to secure a place in the AI-powered future.

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Key Discussion Points & Insights

1. The Scale of the AI Investment Race

• Massive Investments in the US and China: The US and China together account for 90% of the world’s AI infrastructure. Apple, Oracle, SoftBank, and OpenAI are investing hundreds of billions of dollars to build their AI sectors.
  • [01:41] Hannah Mullane: “It may be unsurprising that two countries, the U.S. and China, dominate in this field. Between them, they’re responsible for 90% of the world’s artificial intelligence infrastructure.”
• Other Countries Lagging: Europe and developing nations face capital limitations, instability, and the “brain drain” of AI experts emigrating for better opportunities.

2. The Argentine Perspective – Innovation Despite Constraints

• Improvising with Limited Resources:
  • [03:06] Hannah Mullane introduces Nicholas Volovic, a computer science professor running a modest AI hub in Argentina using repurposed servers from 2012.
• Funding Roadblocks:
  • [04:17] Nicholas Volovic (05:25): “The brightest minds in chemistry, astrophysics, computer science, biology, they go to work for data science and AI companies abroad. And you cannot do anything to get them. What can you offer them? A good hardware? No... a good salary? No...”
• The Sovereignty Argument:
  • [04:38] Nicholas Volovic [sovereignty argument]: “If you don’t have people that understand and can handle that technology, that can adapt that technology, you will always be part of a company or other governments that give you the infrastructure and the knowledge. So it’s a kind of sovereignty argument that we are trying to use.”

3. AI Infrastructure as a Geopolitical Asset

• Strategic Importance:
  • [07:07] Ryan Reynolds (paraphrasing expert opinion): “If you host AI hardware within your borders, it does give a government territorial jurisdiction to, say, impose regulations that can govern and shape the development of these very influential technologies.”
• National Security and Competition:
  • [07:29] Ryan Reynolds (on behalf of Zoe Hawkins, Oxford Internet Institute): “For many, it’s an issue of national security. They might make the argument that with increasing geopolitical tensions, there’s a greater appetite for supply chain resilience and a fear about international disruptions.”
• Policy Incentives: Governments worldwide are deploying tax breaks and incentives to attract private investment for new data centers and AI-focused enterprises.

4. The African and Kenyan Experience – Adapting to Scarcity

• Resource Constraints and Creative Workarounds:
  • [11:31] Shiko Gittel (CEO, Carla, Kenya): “We have to optimize for when there’s low resource constraints... like 4am, 5am ... because then Kenya has not woken up, Europe has not woken up, the US is sleeping... So the only person you’re competing with is China and India.”
• Dependence on Foreign Infrastructure:
  • [13:10] Shiko Gittel: “Most of our data does not reside in Africa. In fact, when you say it, I mean, it was so embarrassing. The claim is we don’t have enough capacity to host all our data here, But Africa has 11,000 data centers. How good are they? We don’t know… right now we are relying on the big tech companies to host our data.”
• Innovation Under Constraint:
  • [14:10] Shiko Gittel: “There’s a team ... that is looking at something we’re calling resource constraint AI, which looks at how do we build AI in our resource constraint environment. But we cannot wait for everything to be perfect. To start playing... We actually innovate for constraint.”

5. Europe’s Push for Tech Sovereignty

• Rise of ‘Sovereign Cloud Providers’:
  • [15:35] Matthias Neubauer (CEO, Exoscale, European cloud provider): “Generally speaking, people and businesses are a little bit worried and concerned if they’re not in full control of something, and political developments in the last couple of months certainly made people more concerned and more worried about having full control of the infrastructure.”
• Infrastructure Gap and Trade Barriers:
  • [16:30] Matthias Neubauer: “Europe and other parts of the world definitely have to step up their game. And it’s not easy because it requires a lot of capital expenditure. And then there’s also things like trade restrictions coming into play. So certain powerful chips cannot be sold to certain countries due to trade restrictions. From the U.S. for example. The world today is the slowest it will ever be.”

6. The Role of Private Companies and International Organizations

• Commercial, not Equitable, Investment Decisions:
  • [17:35] Zoe Hawkins (Oxford Internet Institute): “So these decisions about investments are being made on commercial terms and not being directed on the basis of equity and or even need. ... It’s a much bigger question as to how do we direct foreign private sector companies to invest in places that isn’t their highest return.”
• Global Reliance on US and Chinese ‘Tech Stacks’:
  • [18:38] Zoe Hawkins: “...of the 33 countries that have AI compute, 18 of them relied on providers from either just China or the U.S. so it sort of aligned with one global powers tech stack. So we had 13 countries relying only on U.S. hyperscaler infrastructure, whereas five were relying only on Chinese hyperscalers.”

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Notable Quotes & Memorable Moments

• On Resourceful Innovation:
  • [03:40] Nicholas Volovic (Argentina): “We used very old servers from Supermicro that were from 2012, and we repurposed them adding GPUs... It was the only way to get something related to AI working.”
• On the Reality of Brain Drain:
  • [05:25] Nicholas Volovic: “The brightest minds in ... computer science, biology, they go to work for data science and AI companies abroad. And you cannot do anything to get them.”
• On African Innovation:
  • [14:10] Shiko Gittel (Kenya): “We actually innovate for constraint.”
• On the Relentless Pace of Change:
  • [16:44] Matthias Neubauer (Europe): “The world today is the slowest it will ever be. It will continue to only move faster, and AI will most certainly accelerate that process.”
• On AI Infrastructure Ownership:
  • [18:38] Zoe Hawkins: “When we look at who owns these companies that run the data centers, we found that ... 18 of them relied on providers from either just China or the U.S. ... There was 12 countries ... you could describe as hedging, having a mix of providers from the us, China and Europe.”

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Timestamps for Major Segments

• [01:00] – Episode theme introduction by Hannah Mullane
• [02:01] – Matthias Neubauer on the global infrastructure gap
• [03:06] - [05:49] – Nicholas Volovic, AI hub struggles in Argentina
• [07:07 - 08:22] – Zoe Hawkins on strategic importance and investment decisions
• [11:31 - 14:57] – Shiko Gittel, Carla (Kenya): Working around infrastructure gaps, creative innovation, and the problem of data sovereignty
• [15:35 - 17:12] – Matthias Neubauer, Exoscale (Europe): Sovereign clouds and trade barriers
• [17:35 - 18:38] – Zoe Hawkins: Commercial motives and the risks of global reliance on US/China tech stacks
• [19:29] – Host wraps up with reflections on the future

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Conclusion & Takeaways

• The global AI landscape is dominated by the US and China, who wield near-complete control over infrastructure and investment.
• Countries with fewer resources have to adapt creatively—repurposing old equipment, shifting work hours, relying on foreign data storage, and focusing on innovation born of necessity.
• Increasing geopolitical tensions and national security concerns are encouraging governments to push for sovereignty in digital infrastructure.
• Ultimately, the growth of AI is accelerating rapidly, and only creative policymaking, determined local initiative, and international collaboration will prevent less wealthy nations from being left behind.

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For further insights into AI’s impact around the globe, stay tuned for the next episode of Business Daily’s series on artificial intelligence.

Transcript

[Hannah Mullane]

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[Shiko Gittel]

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[Hannah Mullane]

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[Hannah Mullane]

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[Hannah Mullane]

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[Shiko Gittel]

You don't look like. Please.

[Ryan Reynolds]

I'll take that as a compliment.

[Hannah Mullane]

See it differently when you stream the best of British TV with BritBox. Watch with a free trial today. Hello and welcome to Business Daily from the BBC World Service. I'm Hannah Mullane. Today, in the second part in our series looking at how artificial intelligence, or AI, is changing the business world, we're looking at the growing AI divide.

[Podcast Advertiser]

Well, a big AI announcement at the White House. We're talking about Oracle, SoftBank and OpenAI investing at least $500 billion in artificial intelligence.

[Hannah Mullane]

Apple has committed to spending $500 billion.

[Ryan Reynolds]

In the United States over the next four years.

[Hannah Mullane]

Just a snapshot of the huge amount of investment happening in the U.S. in the race to build the infrastructure needed for AI, it may be unsurprising that two countries, the U.S. and China, dominate in this field. Between them, they're responsible for 90% of the world's artificial intelligence infrastructure. But what does that mean for everyone else?

[Matthias Neubauer]

What we do see is a gap between some countries on this planet versus other countries and regions. Europe and other parts of the world definitely have to step up their game. And it's not easy because it requires a lot of capital expenditure.

[Hannah Mullane]

We'll hear about the impact of this growing AI gap and how some businesses are coming up with innovative solutions to try and keep up, including working when everyone else is asleep.

[Shiko Gittel]

You have to find time when not everybody's hogging their resources, like 4am, 5am because then Kenya has not woken up, Europe has not woken up. The US is sleeping. Yeah. So the only person you're competing with is China and India.

[Hannah Mullane]

That's the AI divide, the haves and the have nots all coming up on this episode of Business Daily.

[Nicholas Volovic]

This is an intermediate place where you just clean your shoes. Here, in order to keep the dirt.

[Matthias Neubauer]

Off, you close the doors.

[Nicholas Volovic]

And this is the first part.

[Hannah Mullane]

Nicholas Volovic is a computer science professor at the National University of Cordoba in Argentina. He's running what counts as one of his country's most advanced AI computing hubs from a converted room at the university. A stark difference from the infrastructure you might find 5,000km away in the US.

[Matthias Neubauer]

Let's enter.

[Nicholas Volovic]

But the noise will be unbearable.

[Hannah Mullane]

Nicholas has been repurposing a lot of old computer equipment to run the site.

[Nicholas Volovic]

We are always trying to push the budget. We used very old servers from Supermicro that were from 2012, and we repurposed them adding GPUs. So we added stuff like that to get a new life to the computer. It was the only way to get something related to AI working.

[Hannah Mullane]

To develop AI technology, you need a lot of investment money that Nicholas says the Argentine government is unwilling to give. And he doesn't have much luck getting funding from private companies either.

[Nicholas Volovic]

We are trying to be imaginative and try to convince the more the state governments or even foreign finance institutions or multilateral banks to get loans.

[Hannah Mullane]

How do you try and convince these institutions to give you the money? And how likely are they to say yes?

[Nicholas Volovic]

The strategy that we use is basically human resources. If you don't have people that understand and can handle that technology, that can adapt that technology, you will always be part of a company or other governments that give you the infrastructure and the knowledge. So it's a kind of sovereignty argument that we are trying to use. That's quite important in a sense, because you cannot control anything if you're using a foreign country or a foreign company. We also try to convince the multilateral banks to lend us money using the same sense we need local development.

[Hannah Mullane]

As Argentina lags behind, the country's workforce looking for jobs in AI end up going elsewhere.

[Nicholas Volovic]

The brightest minds in chemistry, astrophysics, computer science, biology, they go to work for data science and AI companies abroad. And you cannot do anything to get them. What can you offer them? A good hardware? No, you can offer good hardware. Can you offer a good salary? No, you cannot offer a good salary.

[Hannah Mullane]

It's a frustrating situation for Nicholas as he tries to convince the people that hold the purse strings that AI research is worth investing in. The president of Argentina Javier Milei announced plans last year to make Argentina a global hub for AI. He said the country had an abundance of cheap electricity and a highly skilled workforce. He even passed a new law offering tax breaks and other incentives to companies willing to invest in AI infrastructure there. But with an unstable economy and as Nicholas pointed out, a flood of young minds moving abroad to work in the sector, attracting big tech corporations is proving difficult. This strategy is happening all over the world as countries pledge billions of dollars of investment into AI and bring in initiatives to encourage private companies to build their data centers in their countries or competing for that corporate investment.

[Podcast Advertiser]

Chinese tech giant Alibaba launching an advanced reasoning AI model overnight.

[Shiko Gittel]

We aim to mobilize a total of 200 billion euros for AI investment in Europe. The Indian government is preparing to launch.

[Ryan Reynolds]

India AI Compute Portal, a platform that will enable key stakeholders to request computing capacity.

[Hannah Mullane]

So why is it so important?

[Ryan Reynolds]

If you host AI hardware within your borders, it does give a government territorial jurisdiction to, say, impose regulations that can govern and shape the development of these very influential technologies.

[Hannah Mullane]

Zoe Hawkins is a research associate at the Oxford Internet Institute and has been investigating which countries dominate in terms of AI hardware and what that could mean for the future.

[Ryan Reynolds]

For many, it's an issue of national security. They might make the argument that with increasing geopolitical tensions, you know, there's a greater appetite for supply chain resilience and a fear about international disruptions. It's not entirely cut and dry. There's a lot of reasons that are compelling, but it comes with trade offs. Like any policy decision, the reason that.

[Hannah Mullane]

People are seeing this as an opportunity is there is a lot of money in AI, isn't there? They're seeing the future growth of this digital industry and thinking, I need a piece of that pie.

[Ryan Reynolds]

That's absolutely right. From both a corporate perspective, which is exactly what you'd expect. You're hearing people describe it as an AI race. It's certainly motivating people to make big investments. It's also pushing governments to think about it more holistically and have a bit of a strategy around how do we make our jurisdiction really attractive and build out all of these different capacities?

[Hannah Mullane]

Zoe Hawkins, you're listening to Business Daily on the BBC World Service.

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[Shiko Gittel]

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[Ryan Reynolds]

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[Hannah Mullane]

I'm Hannah Mullane and today we're looking at the AI divide. The race for AI dominance between China and the US means these two countries are way ahead of the rest of the world when it comes to AI infrastructure and investment. And while China should close the gap on AI models this year, the US still has a big advantage, with most of the big players in tech choosing to base themselves there. Nvidia, for example, based in the US makes over 90% of the computer chips used by the majority of AI companies around the world. And that's just the start. Earlier this year, President Donald Trump announced the creation of Stargate, a private venture between OpenAI, Oracle and SoftBank, promising $500 billion of investment into AI infrastructure in the US. What happens to other parts of the world that aren't seeing this same rate of it's 3:30am in Nairobi, Kenya's capital, and whilst most of the country is sleeping, software engineers are heading into Carla's offices, an AI startup developing artificial intelligence software for businesses around the world. Kenya doesn't have local computing power for Carla to develop its AI models, so instead they use data centers in other parts of the world. And that often means an early wake up call.

[Shiko Gittel]

We have to optimize for when there's low resource constraints. You have to find time when not everybody is hogging their resources. So we have to optimize that, which is like 4am, 5am, because then Kenya has not woken up, Europe has not woken up, the US is sleeping. So the only person you're competing with is China and India.

[Hannah Mullane]

Shiko Gittel is the CEO of Carla. She's been talking to my colleague Michael Kaloki.

[Shiko Gittel]

When you're training a model, you're sending large files of data to computer system somewhere and then it's processing it and sending you feedback. Now you can imagine if you are 100 thousands of you trying to access that same resource, what will happen. It's like your phone. Yeah. It will say these 15 apps are eating up on your memory. It's the same way. And what I love about the engineers is they found where to host their workloads such that it processes faster because, you know, the further it is, the slower it is. Sometimes they leave it overnight to run so that when Americans have gone to sleep, they're able to run their work. Before Europe wakes up, you're able to run their work. We have a small car, sleeping port, but most of the time people go home and come back in the evening because they find it better to work at that time.

[Matthias Neubauer]

In regards to data storage, is that a challenge? A concern that we have here on the continent, whereby sometimes we have to sort of rely maybe on storing data elsewhere, such as America or other countries, and working with it from there.

[Shiko Gittel]

Most of our data does not reside in Africa. In fact, when you say it, I mean, it was so embarrassing. The claim is we don't have enough capacity to host all our data here, But Africa has 11,000 data centers. How good are they? We don't know. Huawei is encouraging every government to host a data center. Do they have their storage capacity? We don't know because right now we are relying on the big tech companies to host our data.

[Matthias Neubauer]

What do you need to be able to grow as you would like?

[Shiko Gittel]

I know that usually the question for what do you need to grow? Is usually money. Money is a second level priority, first level priorities. Believe. We need people to actually believe Africa has the ability to do.

[Matthias Neubauer]

Now, Africa as a continent does not have the same infrastructure that other parts of the world have. Do you feel like the continent will be left behind?

[Shiko Gittel]

Yes. There's no power. So there's a team, part of our team, that is looking at something we're calling resource constraint AI, which looks at how do we build AI in our resource constraint environment. But we cannot wait for everything to be perfect. To start playing. And that's where the idea of resource constrained AI comes in. Edge computing, which does not mean too much power. You can run a model from your phone. People are becoming creative. That's why he's saying we need to showcase some of these ideas to the world. But we have to showcase by building that ecosystem, building the researchers, building the startups, and it has to start with building that demand. I don't think Africa will be left behind because of our constraint. We actually innovate for constraint.

[Hannah Mullane]

Carla, like many other companies, has to rely on the US and China for its compute power. But as other parts of the world race to compete, will that trend change? Exoscale is a European cloud company. Businesses used to have in house equipment to store things like computer programs, emails and apps. They now use companies like Exoscale who can hold all of that stuff on the cloud. And if your business grows, you just increase your cloud space, which makes it easier to scale up and down. It's seeing more businesses looking for a local company to look after their data. Matthias Neubauer is the CEO.

[Matthias Neubauer]

While generally speaking, people and businesses are a little bit worried and concerned if they're not in full control of something, and political developments in the last couple of months certainly made people more concerned and more worried about having full control of the infrastructure. So they certainly want to avoid that someone pulls the plug. They certainly want to avoid that someone has access to data that they should not have access to. And this is where more and more businesses are turning to sovereign cloud providers.

[Hannah Mullane]

From Europe, we know that when it comes to AI and sort of the digital future, China and the US are the big players. So is Europe going to have to catch up in terms of providing that infrastructure and having the data centers and the companies here that are capable of doing what businesses need them to do.

[Matthias Neubauer]

What we do see is a gap between some countries on this planet versus other countries and regions. And what we also see, the AI is becoming more and more critical. Europe and other parts of the world definitely have to step up their game. And it's not easy because it requires a lot of capital expenditure. And then there's also things like trade restrictions coming into play. So certain powerful chips cannot be sold to certain countries due to trade restrictions. From the U.S. for example, the world today is the slowest it will ever be. It will continue to only move faster, and AI will most certainly accelerate that process.

[Hannah Mullane]

We might be seeing more companies looking for more locally sourced digital infrastructure, but that simply isn't possible in all parts of the world and governments might be able to bring in policies to try and persuade private companies to bring their AI businesses to their country. But ultimately it's down to those massive corporations as to where they spend their money. Back to Zoe Hawkins from the Oxford Internet Institute.

[Ryan Reynolds]

So these decisions about investments are being made on commercial terms and not being directed on the basis of equity and or even need. It's a much bigger question as to how do we direct foreign private sector companies to invest in places that isn't their highest return. International organizations, whether that's the UN and other development organizations, the World bank and similar, are very much viewing this as a development issue and agitating within this space and particularly with some of these larger companies to try and encourage them to factor some of those elements in to their investment decisions. But ultimately maybe it's a case of what are the policies and investments that can be made locally. And this is where the pressure comes in for governments to compete with each other almost for these companies investment. And that's why we see such a cascade of different strategies and incentives and policy settings trying to make their own jurisdictions the place that these private sector entities want to put their money. It gets even more interesting when you look at the ownership of this unevenly distributed AI infrastructure. When we look at who owns these companies that run the data centers, we found that of the 33 countries that have AI compute, 18 of them relied on providers from either just China or the U.S. so it sort of aligned with one global powers tech stack. So we had 13 countries relying only on U.S. hyperscaler infrastructure, whereas five were relying only on Chinese hyperscalers. There was 12 countries that are sort of, you could describe as hedging, having a mix of providers from the us, China and Europe. That trend for me is also one that will be interesting to watch. Are more countries sticking with one tech stack or is there more of a hedging as uncertainty in terms of the global order of things comes into question?

[Hannah Mullane]

All the data points towards the US and China continuing to dominate in the AI market. But as more innovation happens around the world and more demand for localized digital infrastructure continues to grow, we might start to see some changes. The reality is AI technology is moving so fast that it can be difficult to predict exactly what the future holds. What we do know is the industry is going to continue to grow, which means its economic potential will grow too. That's all from this episode of Business Daily, produced and presented by me, Hannah Mullaines. Tomorrow Samir Hashmi will be in the United Arab Emirates, which is setting its sights on becoming the world's next AI powerhouse. If you'd like to hear more on our AI series, just search for Business Daily. Wherever you get your podcasts.

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