301. Why the US won't stop China in the AI race

16:45Azeem Azhar:So this is like a digital version of Belt and Road. It's a digital version of Belt and Road. I think it's perhaps closer to Bandung, 1955, the Bandung announcement where Kwame Nkrumah talked about trying to establish a third nation sovereignty of some description when you were facing the Soviet and the US blocs at the time. I think it felt a little bit more like that than a straight on Belt and Road because Belt and Road had with it physical infrastructure, capital investments and all of the controls on capital that emerged from it. It was a much, much more controlling structure, whereas this was, you know, I think a challenge that I would hope that the West, the US and the UK would rise to also meet with their own offerings of open source and capability export rather than just sort of leave it to one side.

17:42Robert Peston:If the West ignores developing economies, emerging economies, and simply leaves it to China to export their AI to, as I say, these growing nations, what's the implication of that?

17:59Azeem Azhar:I think it could be extraordinarily challenging because you lose the soft power battle in the first instance. And soft power has been so useful for the West for the last 50 or 60 years. You also lose access to the technology stacks as a market that gets lost because today these models run predominantly on American chips from NVIDIA and AMD. But China has responded to the chip constraints over the last few years to start to build their own chip capability. So you may find that you'd go into some of these countries and every element of what we call the stack from the application to the model that's being run to the chips and also the power that's being provided by the Chinese solar panels is top to toe coming from China.

18:47Azeem Azhar:And that is a bond that is commercially and strategically hard to break.

18:51Steph McGovern:I wanted to ask on that about the power side of it, because obviously that is probably the biggest operational cost for them. So is the companies who will do well or are doing well, the ones who are thinking as much about the energy generation capability as they are about the tech and the chips?

19:09Azeem Azhar:It's all about power right now. All of these chips need electricity to run and to give you a sense of the scale. The latest NVIDIA, it's not a single chip, but it's a series of chips that you buy in a block, needs about 100 kilowatts. So that's about running 50 kettles at full tilt. And it's an extraordinary amount of electricity. And so securing the power has been the thing that has been first and foremost on the AI companies. and time to power is the thing that they care about the most. They're willing to pay a premium in order to get energised, as they call it. So you can't get a... What is 100 kilowatts?

19:52Azeem Azhar:Well, 100 kilowatts is manageable in most places, but a data centre five years ago might have been 50 megawatts. The data centres that are being built today at 500, 750 megawatts up to a gigawatt, and that is utility scale. That's like a big aluminium factory amount of power. And so the AI companies are now out there first and foremost trying to figure out how to secure power for their data centres. And that is the deciding factor. If we think about what that means in the UK, we could be more well positioned, but we're not really because there's this enormous queue to get connected to the grid.

20:33Azeem Azhar:the area where most of our data centres currently live, which is this corridor from Shepherds Bush in the west of London, past Heathrow out to Slough, is the most congested electrically. You'll remember there was a power outage at Heathrow, which is the last place in the country you want a power outage. And there, I don't even think you could probably add a kettle to the grid without something terrible happening, let alone an AI data centre. So it really is a lot about power now.

20:58Steph McGovern:So how do you get past that then? One of you know, you've just mentioned there the problems we have here. What can you do about it?

21:06Azeem Azhar:What's happening in China is that they've had an electrifying electrical system. It's growing incredibly quickly and they've solved their power issues. In the US, it's a much, much harder problem because the US power system has been, the word I used in a report I did recently, moribund for about 15 years. In other words, after 100 years of growth, it just went flat and the company started to extract profits rather than invest in infrastructure and growth. So there's been this injection of demand. Any place that can get a connection, its price is going up very, very significantly. The second is that if you can, you will just energize whichever way you will.

21:50Azeem Azhar:So that might be diesel generators, which are dirty, locally polluting, expensive and chuck out loads of CO2. There might be gas turbines, but now there's a 24-month backlog to buy gas turbines. It might be to invest in renewables, and we've seen some enormous renewable farms, and finally nuclear. And so there is now a resurgence of nuclear in the US, but it's a very, very slow process. That particular part of the power industry is like wading through molasses.

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24:05Robert Peston:Obviously, one of the things that's been on people's minds for a good year now is whether there's actually a bubble in this incredibly important area of economic development. You have recently published a very influential report where you did something unusual, which is you actually did micro research. You went and, as I understand it, talked to all the important players. And your view is that there isn't a bubble, that actually the revenues that are coming down the pipeline do justify the kind of investment we're seeing. Is that right?

24:45Azeem Azhar:I'm going to allow myself to nuance it. I mean, you know, bubbles can emerge for lots of reasons. And there could be a bubble that emerges here. But on the specific question of are revenues from customers into the AI sector currently growing rapidly? and have they started to meet some of the depreciation expenses of this multi-hundred billion dollar build-out. The thing that surprised us was that at the end of 2025, they crossed that mark. They just started to cover the depreciation expense and that's quite important. I can give you some numbers there.

25:30Robert Peston:And this is cash or this is accrual accounting?

25:36Azeem Azhar:No, this is cash. So in the 12 months to 2026, the amount of revenue generated in the AI sector exceeding China was$110 billion. And that is controlled for duplication, you know, for spending$100 with Anthropic, who then spends 50 with Microsoft. That's not 150 in our book. That's 100. And that's a 3.5-fold growth over the previous 12 months. and it was growing, still growing at that pace. So we estimated that although it was$110 billion in the previous 12 months, if you annualise June, you get to$175 billion.

26:18Steph McGovern:And that is faster than other things like, you know, mobiles coming in, early internet.

26:24Azeem Azhar:Yeah, if you look back at mobile apps and the internet or the cloud hosting, I think it's about three times faster than those particular waves were to this$100 billion annual mark.

26:36Robert Peston:If you look at the investment that is taking place now and committed for the next few years, are you saying that if revenues continue to grow at this rate, that that is justified expenditure? or are you building in some conservative assumptions that at some point the revenue growth will slow down?

27:04Azeem Azhar:Well, I mean, if it grows at this rate, it would just be a very odd situation, but it would be a very good investment. I don't think it will grow at this rate. I think it will slow down. These things have to. The question is when and at what point. And if you look at the level, I mean, if you think about what has to be paid back, you have to pay back the depreciation expense on all these chips and the cooling and the power and the building. And you also have to pay the operating expenses, so the electricity and the staff. And then you have to make a profit because you've got other costs outside of your gross margin, your marketing team and so on.

27:46And finally, your shareholders aren't investing in a charity, so they want their return.

27:51Azeem Azhar:So if the total stack of the depreciation expense is, say,$250 billion, which it might be in the...

28:01Robert Peston:That's a lot of depreciation.

28:02Azeem Azhar:It's a lot of depreciation. That's the sort of range it might be in 2028. It'll actually be slightly higher than that. Wow. If you wanted to have a fully sustained market, you'd expect to see$400 billion,$450 billion of revenue come in. That will pay the depreciation expense. It'll pay power. It'll pay salaries. it'll leave a profit. And is that a reasonable projection for 28? Well, we'll end the calendar year of 2026 between$185 and$190 billion. And it's harder to forecast 2027, but I do think that for it to get towards$300 billion is not unreasonable. I mean, we have more detailed forecasts.

28:44Azeem Azhar:The range is quite wide. It could be$250, it could be$350.

28:47Robert Peston:And just to be, I mean, before I get on to some of the risks around all of this, because these are huge numbers. So we're talking about 300 billion by when, did you say? The calendar year 2027. And when, I mean, just so that people can understand this this year, sort of extraordinary development of this industry. When in effect were they nought? Oh, 2022. So 2022, you know, literally five odd years. We're looking at$300 billion.

29:24Azeem Azhar:Well, American and British businesses are still by and large dabbling. I think that's one thing for us to understand.

29:32Steph McGovern:You mean the people using it?

29:34Azeem Azhar:Yeah, the people, the customers who are paying OpenAI and Anthropik and all these other businesses are mostly dabbling. The average US business spends$11 per employee per month on their AI tools, which is not a huge amount. And very few US companies have yet come out and said, this AI thing has completely transformed our economics. You're getting the first signs. So Bank of America, Goldman Sachs, these are the easiest businesses in the world to do this in because it's finance, it's digital, you're not moving stuff around. And they already spend a lot on AI and they make money very quickly. That's what a bank does.

30:13Azeem Azhar:So you've got the first signs of companies getting to results that they're willing to talk about. But one of the things that's difficult, Steph and Robert, is that CEOs are under so much pressure to prove that they can use AI. They're talking about it a lot. So we talk about we track earnings transcripts and about 30 percent of American CEOs talk about how they're using AI and their earnings. You have to then do some picking apart to say how much of that is just job protection and how much of that is is real. and you know when i talk to ceos i talk to you know in the order of 100 in europe and the uk and the us every year i hear a pretty common message back which is they're committed they're getting some early results it's much harder than they thought and they don't intend to slow down because they're learning and they're figuring things out and their ambition is growing is it

31:10Steph McGovern:a case that because you know obviously we talk to business bosses a lot it feels like there's a There's a kind of divide between the CEOs and the businesses who are getting their staff to use AI to kind of improve their productivity. And those that are looking at it from a transformational point of view. And how do you bridge that? So it's not just about efficiency for workers, but it is about how you use it to totally transform your business.

31:36Azeem Azhar:Total transformation is very difficult. With electricity, it took 25 to 30 years in the US because you have to completely change the way a factory works. And that just takes time. What the AI companies have started to do is they have set up joint ventures of professional services, of like management consultants. They're called the deployment company, for example, is the OpenAI one. And it's got billions of dollars from private equity and from OpenAI itself. And the job of those businesses is to go into established firms and do that transformation that you've talked about on the basis that you need both all of the intimate knowledge that a company has and this outside thinking that AI companies have.

32:23Azeem Azhar:So that's the theory. And I'm sure it looks really good on a slide. We'd have to see if it actually works and how long will it take to work.

32:32Robert Peston:But there's a related point, which is I, and I'm sure like you, know quite a number of people who've set up essentially AI only firms in specific sectors. So in law, for example, I know a couple of new law firms that are essentially employing almost no lawyers and offering but sort of standard services. So, you know, in things like libel law.

33:04Steph McGovern:Will writing. All that kind of stuff.

33:07Robert Peston:And so it seems to me the issue is if these almost one man bands, but offering really quite a comprehensive service were to take off, then if the existing firms don't totally re-engineer, they're going to be out of business, aren't they?

33:25Azeem Azhar:Well, look, something like will writing is very, very low-hanging fruit. And for years, you've been able to buy a will for£10 on the internet. The reality is that most law is not like that. And the large part of the expense is more complex employment law issues or it is transactions. And what law firms are starting to realise is, and it's not just law firms, it's also software developers. You speed up individuals, but you don't speed up the team. What you do is you create congestion because we're all so busy, but it has to be verified and signed off by somebody. And that's particularly true if you're a law firm because your job is essentially to be the liability sponge for your client.

34:10Azeem Azhar:And so the process speeds up as fast as its slowest component.

34:16Steph McGovern:Also, I've got a mate who's a wills and probate solicitor and she spends most of her time dealing with emotional people. Right. At the end, dealing with wills. So there's that as well, which is, yeah, OK, I can help her speed up, do the legislative side, but not the actual dealing with these emotional clients on the phone.

34:35Azeem Azhar:Right. And that part, I think, stays, is very hard to see how that gets affected over the years. In fact, it might get improved because she may have more time to talk to them. But I talked to a manager in a actually, funnily enough, in a company that works in AI. And she said she's got a thousand engineers and every one of them is about 30 percent more productive. But as a whole, the group is perhaps 10 percent more productive. And what's going on? Why is 1.3 times a thousand not ending up where it should be? And it is that problem of of congestions and bottlenecks because we've built all of our internal systems for an assumption about how fast people work.

35:19Azeem Azhar:You know, Robert, you're you're extremely ferocious with your essay writing and your tweeting and so on, because you go direct to the audience. But imagine if there was a traditional newspaper chain of sub editors and editors to sign that off. They wouldn't be able to cope with with your the speed with which you produce. And I think the thing that companies need to do to get to Steph's question of transformation is how do you get around or change the way you verify and approve and make decisions? And companies are not bundles of tasks. The task is one part. Companies are actually people sitting around agreeing to take a risk or not take a risk.

35:57Azeem Azhar:And that process still takes time.

35:59Robert Peston:It does take time, but even the verification process can, in a sense, be delegated to AI. And so all of these bottlenecks, I'm not saying this is a good thing, but all of these bottlenecks can be massively dealt with, speeded up.

36:19Azeem Azhar:They can be cleared. Over time, they'll be cleared. And I have my own experiences with my own work where I have now verification systems, which are many different AIs.

36:33Robert Peston:That's right.

36:34Azeem Azhar:A little bit like a series of muslin gauzes. And if you overlay them all, they go from being translucent to opaque. And that's what I've done, which sort of saves a little bit of time.

36:46Steph McGovern:So just in practice, can I ask how that works? So you will do something and then you will put it into lots of different AI systems.

36:54Azeem Azhar:That's right.

36:54Steph McGovern:And then how do you know which is the right one?

36:56Azeem Azhar:So what will typically happen is I will I will have written something up and I will put it into two different AI systems. One might be Claude and the other might be a ChatGPT set of agents to do some fact checking. and if they disagree on any facts in any degree or any argument then that goes to a judge that will go off and check and the agreement level depends on how consequential this is sometimes it's just the number sometimes they have to agree both on the fact and the academic article that it's that it's come from and that can just run that just runs that's robert's bottleneck being cleared there and then I end up with a like a log that is the list of facts and a list of articles that these come from what the agreement level was and I can walk through that and say just like an auditor the senior auditor at the end of an audit and say I want to dig into this a bit more

37:50Robert Peston:but also the marginal cost of the checking is more or less nil whereas the marginal cost of a human checking is whatever that person is being paid so you know the productivity savings here are immense

38:02Steph McGovern:But it means trust, though, doesn't it? That's the thing. That's the key here is like businesses and business leaders have got to get to the point. Our team managers, whoever it is, in the case of your friend who's the engineer with a team of engineers, you've got to trust that that is right, haven't you? And that's where we're not. We're not there yet.

38:20Robert Peston:So there are these enormous imponderables, the rate of rollout in established businesses, how effective in the end this rollout will be for these businesses, which takes one back to this issue. You know, this not unimportant issue about whether there's a bubble. You will presumably have seen the fairly detailed academic or effectively quasi academic paper by the Bank for International Settlements. And we just remind listeners that the point about the BIS is it does have a pretty good track record of identifying bubbles. and most famously of all, it was a very lone voice for a while among international regulators in the run up to the 2007-8 financial crisis and the BIS was an early and important voice saying there is a very serious bubble here and we're looking at the potential for a big crash that's going to harm the economy.

39:30Robert Peston:Now, as I say, they have put out a paper where they are saying that on their model, the level of capital investment at the moment is significantly greater than what you might call the equilibrium rate, which means that there is in their terms a very significant risk, well, not so very, but a significant risk that we are going to get a crash.

39:50Azeem Azhar:We may well get a crash. I mean, if you think about the scale of investment that is going into this, it's going to be into the multi-trillions of dollars by the end of 2030. And that is really, really hefty. And if you look at the amount of capital investment that's gone on in the US as a percentage of GDP going back to really the 1920s, which is when the data set is available, this year will be close to the highest year ever, which happened to be, I think, 1930. So when GDP was heavily depressed after the Wall Street crash, next year will almost certainly be higher. So these are things to look at because this is what economists call a shock.

40:36Azeem Azhar:It's a shock to the system. And certainly the health of this entire system is not as strong today as it was a year ago when I started to formally track the bubble risk. the revenue is very very healthy far ahead of where we expected it to be but that's not the only factor in where that where a risk starts to emerge and you know where where would that where would that come out the the real tell and you know of course robert you know this from the global financial crisis and the housing crisis is when financing structures are you know borrow short for a long investment. So what classically happened in the US was that homeowners were taking two-year interest-free mortgages and then moving on to ARMs, adjustable rate mortgages, and that's when the defaults happened.

41:31Azeem Azhar:Once financing starts to take that kind of characteristic at scale, in this market, you would start to get quite nervous. In other words, It's people lending, borrowing for five years on a 20-year asset.

41:47Robert Peston:In these sorts of situations, what typically happens is you'll get a business that says we're growing at this kind of rate. And we've got these contracts in place for our services. And what they tend to do is then, you know, discount those revenues back to get a present value and then borrow against that de facto security of those supposedly contracted revenue schemes. How secure are those contracts?

42:19Azeem Azhar:I mean, some of them are much more secure than than others.

42:23Robert Peston:Because there's obviously a point of risk there that at the point that, you know, any individual business says, actually, this is not working out for us. Right. Contracts get cancelled.

42:33Azeem Azhar:There's this number called the RPO, the Revenue Performance Obligation, that gets spat out. And these numbers are getting so large that you can't fit them on the calculator that your kids would have used for their GCSE. and there is, you know, inherent in that, there is some risk because it's a contingent on a number of things that might play out and we're at$110 billion annualised over the last 12 months and we've barely touched the surface of the FTSE 500 or the Russell 2000 in the US. In terms of sales. In terms of sales, right. There's a lot of room for that to grow and so I think the risks emerge elsewhere And I think they emerge from what might happen within, you know, within financing structures and financing arrangements and try to work out whether there are things that are not just the occasional deal that looks bad, but something that is sort of a common pattern that's emerging.

43:32Steph McGovern:Because there's been quite a bit of scrutiny in the way like NVIDIA has been financing companies that are then using the chips. And there's been lots of talk about, is it like Enron with the special purpose arrangements? What's your thoughts on that? Because there are people who think that looks a bit dodgy.

43:50Azeem Azhar:Well, look, I think people have, there are two rough camps about AI. There are those who think it's going to create the machine guard and there are those who really hate it. And depending on your camp, you will have already made your decision. So, you know, I'm going to talk about what the middle looks like. Think about a market that's expanding really quickly. And it's expanding so fast that people providing services in that market don't have the capital to serve their customers. But their underlying supplier has got an incredibly strong balance sheet. Perhaps its five-year bonds have got a better credit rating than the U.S.

44:28Azeem Azhar:Treasury, which is the case of NVIDIA. It would make sense for the businessman to lend his downstream customers in order for them to serve their customers. And that would feel really, really normal in most other industries, except in ones where people have this, you know, Spurs Arsenal division about which side they're on. This happened in the US in the 20s with auto finance as well. So, you know, General Motors didn't just provide higher purchase or financing packages for consumers. They also financed the dealerships. Now, every historical analogy is only as useful as you can stretch it. So there's lots of things that are going on today that are without precedent.

45:13Azeem Azhar:But without precedent just means that we can't go back and look at a data set to say, how did these things work out in the past? At the end, what we see is that the chips that NVIDIA give out to people or sell or invest in companies and then they buy those chips are used at extremely, inordinately high levels. They're mostly on six-year depreciation schedules. When we talk to people in the market, they tell us, well, after six or seven years, these chips are still commanding premium rents.

45:45Robert Peston:Right. And so what that suggests is that as long as that demand is still there at the front end, those chips will get used and the risk is...

45:58Azeem Azhar:Demand for AI services. Demand for AI services is there because it means the chips have to get used. If that demand softens, then the chips start to be underutilised. And then you might start to see write downs. You're looking at losses. You're looking at losses and you're looking at write downs and then you could see things unwind very quickly in a slightly disordered way.

46:19Robert Peston:And I guess we should wrap up. The part of all of this that does really worry me and is analogous to 1929, but is not, you know, in a sense, an issue of hard data, but it is one of sentiment, is just the. extraordinary, irrational enthusiasm, particularly among individual retail investors about all of this. So I was genuinely shocked and really quite worried by the trading in, you know, the Musk IPO in the days after that, because that was that was just nuts. And that was just that thing that we did see in the 20s. which is, you know, if you don't get on board, you know, you're going to miss out and all completely detached from any actual rigorous analysis of what cash flows are likely to be like or the strength of the balance sheet.

47:39Robert Peston:This feels like the 20s to me, which is basically, you know, these pools, particularly of US savings, just being channeled into what they think is, you know, the gold mine in a totally, you know, vibes based way, nothing to do with serious investment analysis. And it's the weight of money going in from retail that really worries me.

48:08Azeem Azhar:The Koreans have been through their 1929 moment. So the Korean market is very heavily invested in the semiconductors that power the AI chips. And there's been a 40 % decline in the KOSPI in the last couple of weeks. And 4 % of Korean households had what's known as a margin call where they've been overexposed through leverage and the guys knocked on the door. And that was the shock. But, you know, the Korean market is extremely retail driven, much more so than the US market. But you have seen exactly what happens when the exuberance gets irrational and then nerves take root. If we come back to the concern that you raised, I think there's something to learn from the Korean market.

48:51Azeem Azhar:The regulator moved really slowly to stop leverage around ETFs. And there's some questions to why wouldn't you have done that three or four months earlier. So there are certain breaks that can be applied. I think the other thing that's worth noting is that US banks tier one capital is extremely healthy right now and certainly compared to where it was in 2007 and 2008, very, very under leveraged. There is quite a lot of leverage in the U.S. financial system sitting with hedge funds, investing more broadly, which I think of more than the retail risk as a risk because they're very, very overexposed.

49:27Azeem Azhar:They borrow from only a handful of banks and they can unwind very rapidly. So I would agree with you. There are lots of these risks that are there. When I look at the metrics that we track, things look healthier because of revenue. They look slightly less healthy because of the way financing, especially the debt financing sits. Valuations don't look too aggressive at all across the NASDAQ. There are exceptions. SpaceX was one briefly. But across the market, they don't look particularly hairy. so the patient is for me I would if I had to give it a rating is still reasonably healthy perhaps not as healthy as it was a year ago but but not yet at a point where I have to call 999 but I wouldn't rule out having to do that at some point that's probably a good point to end things

50:23Robert Peston:on isn't it yeah yeah let's hope the heart attack isn't next week the same thank you so much we

50:29Steph McGovern:could chat to you for hours on all of this I love the fact that you've got a million grafts in front of you as well.

50:34Robert Peston:Just in case.

50:35Steph McGovern:Yeah, thank you, Izzy. That's it from us and the rest is money. Bye-bye. It is.

50:38Robert Peston:Goodbye.

50:48Azeem Azhar:I see you.

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