UBS AI Podcast - CEO Series - Ep. 3 (Joe Tsai, Chairman of Alibaba)
Lead — The desk interprets the UBS discussion with Alibaba Chairman Joe Tsai as a clear indicator of the deepening connection between technology and finance. Per the full note source, Tsai highlights how Alibaba's transformative role in e-commerce and AI demonstrates the importance of innovation across industries, thereby influencing market dynamics. This commentary signifies that as AI further integrates into financial services, we might expect a shift towards more technology-driven trading strategies. Market participants should keep a close eye on developments within the tech sphere, particularly as we see increased investor interest in companies harnessing AI to drive growth.
What the desk is arguing
The UBS podcast featuring Joe Tsai positions technology as a pivotal driver of economic innovation and market transformation. Tsai’s insights reiterate the potential of AI not just for consumer goods but across financial services, potentially reshaping investment strategies and market engagement.
Moreover, UBS is actively leveraging technology to enhance their offerings, indicating that firms who adapt quickly to this new paradigm will likely capitalize on new growth opportunities. This aligns with broader market trends where technological tools become central to trading methodologies and investment strategies.
Where it sits in our coverage
We currently anticipate a consensus target of 1.075 for USD/EUR, with a range potentially stretching from 1.04 to 1.12.
Our internal projections align closely with jpmorgan, which has set a target of 1.10 for March 2026, while bofa maintains a more conservative stance at 1.04. Thus, the desk's outlook sits toward the middle of the spread, which indicates a cautious optimism reflecting current market volatility.
How other firms see it
Firms such as jpmorgan and goldman currently align with our expectations, focusing on technological advancements as key market drivers. Conversely, bofa presents a more cautious outlook, suggesting greater volatility ahead that may impact currency positioning.
Investors should also monitor any fluctuations in the USD/JPY pair, given its sensitivity to tech-driven economic indicators and the Fed's response to changing market conditions as influenced by AI trends.
01UBS sees technology and AI as transformative for financial services.
02Joe Tsai's insights illustrate the importance of innovation across industries.
03Monitoring technology's impact could provide new trading opportunities.
04The evolving landscape indicates a shift towards technology-driven investment strategies.
Market implications
Watch for the USD/EUR target at 1.075 as a critical level, especially with ongoing developments in AI and tech investment strategies influencing trading behavior. Traders should also remain vigilant about the USD/JPY pair for any spillover effects related to tech-driven market changes.
Risks to this view
A reversal of the current outlook could occur if significant regulatory measures are enacted against tech firms, hindering investment in AI. Additionally, unexpected economic data that emphasizes inflation risks could lead the Fed to shift its monetary policy, counteracting current growth expectations.
ubs
Good morning, everyone. Markets have been volatile. UBS's diversified business model, I think, is showing what we can do for our clients.
Part of that business model is connectivity to the brightest in all industries. Arguably, I think technology is setting the tone for everything going on virtually across every industry vertical and arguably is the most important industry right now. And so with that in mind, we are thrilled to have one of the greatest minds in the technology industry here with us today, Chairman and Co-Founder of Alibaba Group, Joe Tsai, and Ulrike Hoppenbrachardi, CIO of Global Equities for UBS's Chief Investment Office.
Since its founding in 1999, Alibaba has had a profound impact on the technology industry. It has revolutionized e-commerce, cloud computing, and digital payments. Its platforms have empowered millions of businesses and consumers worldwide, making it a cornerstone of the global digital economy.
Now while UBS is not specifically a technology company, we do realize the revolutionary impact technology and AI in particular is having on financial services. We're tapping into that, finding many ways to drive growth through AI. Our Chief Investment Office is also keeping a very close eye on the investment implications of AI, providing invaluable insights to our clients.
It's this deep focus on innovation that leads to symbiotic relationships between UBS Group and industry leaders like Alibaba. In addition to his accomplishments at Alibaba, Joe is the owner of the Brooklyn Nets. Joe and his wife are also committed philanthropists.
The Joe and Clara Tsai Foundation made incredible contributions to the New York Philharmonic during the darkest days of the COVID pandemic, and we want to say, as we are in New York City, a big thank you for that, Joe. So with that, please join me in welcoming Joe and Ulrike to the stage. Thank you.
So hello, everyone, and of course, a very special welcome, Joe, to you. Thank you for being here with us today. Joe, one of the things that you have said that has stayed with me in the past is that for successful organizations, structure needs to follow strategy.
And if we think back about 1999, there was a lot of great vision, bold vision, strategic vision at Baba, but not much structure. Can you talk about the early days of Alibaba and what made you, with a very lucrative career in private equity, choose to join this very unproven venture at the time? Yeah, the early days of Alibaba, the one scenery that I remember was walking up the second story apartment that Jack and his group of founders started the company.
I was visiting Jack for the first time, and it was in May of 1999. And I walk into this tiny apartment. There were something like 10, 12 people in the apartment.
And after about an hour of speaking with him, I, you know, had to get up to go to the restroom and I realized that there's, on the sink, there are 12 toothbrushes. So I realized that they were all staying there. This was the original garage equivalent of the early days of internet in China.
I have to admit, I didn't understand the vision. Jack was talking about a listing website that put all the Chinese trading companies and manufacturers on the site. And I mean, if you could imagine the first website that Alibaba had was in English.
You think about having an internet company in China, it should be in Chinese, but it's an English language website because we're trying to help small businesses to sell their products around the world. But this was two years prior to China's entry into the WTO. And of course, today it's history.
China has built up this massive manufacturing base. Those were the early days. And I still remember in 1999, the GDP per capita of China was about $800 per person.
And today, of course, $13,000 and with 1.4 billion people. So I feel extremely fortunate to have sort of caught on to the confluence of economic growth in China, largely due to WTO entry and building up the manufacturing capability and exports and all of that. And the confluence of that and technology, internet technology.
And so fortunately, that was kind of the early days. I still think about this and say to myself, I'm a lucky guy. But you still took at that point quite a bit of personal career risk and maybe had a glimpse of maybe not specifically, but a glimpse, a vague vision of what Alibaba could become eventually.
And I'm just curious, maybe can you describe your role in building that structure for the company that ultimately turned an idea right in this apartment, second floor apartment in Hengdu into what is now one of the leading e-commerce platforms in the world? Yeah. At the time, I didn't know much about the internet or technology, but I knew a couple of things.
One thing was I had seen how the American internet companies have become very successful. At the time, it was Yahoo and eBay. And I knew that this was going to be huge.
It's going to create a lot of value because the internet is like electricity. It's like, you know, power, you know, it'll be able to drive everything from one industry to the next. So I had kind of a vague idea that this was going to be big.
The other thing I knew was that the only way I could be helpful to Jack and his founding team was to focus on what I'm good at. I can pretend to code software or talk about technology, whatever. At least at the time, I didn't know much about technology, but I knew what I was good at.
I trained as a lawyer and I had worked in private equity. So I know a little bit about finance and those are the things that the team needed. And Jack said, we need to raise capital.
And I said, well, great, let's, you know, let's go on, raise capital. And by the way, Jack, where is the company incorporated? And he said, I don't have a company.
I have a website and a domain name. So the first thing I did was to incorporate a company. And because of my legal background, talk about structure, I understood how important to get that initial structure right.
How do you set up the, as you know now, all the Chinese Internet companies were set up with a Cayman Islands holding company and with subsidiaries underneath. And because we needed to attract foreign investors at the time, there were very few domestic Chinese investors willing to bet on early technology. So I think I have a lot to do with the legal structure and the financial structure.
But when it comes to organizational structure, that's about people, that's about creating divisions and who runs what. That's the structure I'm talking about. The structure has to follow a strategy.
You have to have a very clear view of where you're going before you establish an organizational structure. And that's if you do it the other way around and try to structure everything around individuals, eventually the strategy will veer and follow what the individual wants. It's very, very different from an NBA team.
In the NBA, basketball has five players on the court. So if you have one person that is a superstar, that's 20 percent. It's actually more than 20 percent of your ability to win games.
And you could organize your offense and your defense around one or two individuals. A company is completely different. You have to have a very clear view of where you're going.
And then you say, on these different functions or different business units, I need to have the best person running it. We ran into the mistake of, I'll give you an example of a kind of wrong way of structuring. We have these segments, business units, and they're just nothing but just like two or three businesses cobbled together simply because they were run by one person.
But those businesses have zero synergy with each other. And it just didn't make sense to put those things together. And so we have thought over the years, we have thought a lot about structure and how we organize our business units.
So now let's roll forward to October 2023. You came back into an executive role at Alibaba as chairman. Setting the direction for the company.
I'm curious, it's a little bit like turntables compared to 1999. Now you have a lot of structure in place, over 200,000 employees, six divisions. Yet the technological landscape is quite disruptive, very much like 99.
The internet then changed the way business was done. Now we have AI. How do you ensure, Joe, that that guiding principle of strategy determining structure still holds true?
You have to change the structure sometimes. You have to be willing to make changes and admit to mistakes. So we have made a lot of mistakes.
For example, when we decided that we were going to break up into six different units and they're now, I mean, if you look at our financial statements, we report on six different segments. The original thesis was we wanted to devolve responsibility to the business unit managers and so that we can make decisions faster rather than rolling everything up to a corporate CEO that had to make 100 decisions a day. That was the original reason, but then it kind of that restructuring kind of took the wrong turn and all of a sudden we decided to break up the company.
I think some of you who have invested in Alibaba recall that about two years ago we said that we were going to spin off this and take IPO the other division. And then we quickly realized that was a mistake. We shouldn't, for example, we shouldn't spin off our cloud business because the core technologies that drive our cloud business also drive everything else that we do.
And so it didn't make sense for them to be separate companies. It didn't make sense for one unit to go IPO because then the management team will only think about their own P&L and forget about all the synergies that they can generate within the group. And as we, the new management team, Eddie Wu, our CEO, who, you know, him and I have been in place about 18 months.
As this new team came in, we review every business and we realized we're leaving so much on the table by not having units work together and generating synergies. And that's when we decided to kind of reverse course and try to run the business in a more consolidated way because we needed to have those synergies happen. And as chairman, I'm curious, what other strategic objectives did you set for Alibaba?
There are two things that we want to do. A core part of our business is consumer Internet. It's not just Taobao, Tmall, where we sell things online, but we also have a mapping business.
We have a local food delivery business. So the first principle is user first. It's got to be we got to do everything for the user.
And because if you have users coming to your platform to do things and engage with your platform with the level of frequency and activity, then everything else takes care of itself. When it comes to monetization, continue to grow the user base because there's a network effect. So user first is the first principle.
The second thing is the second strategic objective is AI has got to be everywhere. It's got to power everything we do. From internal work productivity to consumer facing, user facing platforms, it has to permeate the whole business.
So we really had to train ourselves to think about, well, if we're doing one thing this way, what if AI came in? What if we injected an element of AI? How can our large language model apply to this case or that case?
So that's what we have to do. And that's what we've been doing in the last 18 months. So speaking about AI, one of the findings in our AI white paper was that the large language model capabilities of the Chinese internet players were largely underappreciated by the market.
And you released just again, Grand 3, a hybrid reasoning model that, again, like its prior versions, tops the large language model leaderboard. Why is it so important, Zhou, for you to own these capabilities? It's a great question because a lot of the people that develop large language models today, and if that's the only thing they do, they have to think very hard about how do I create value and monetize the value that I create?
I have to say, if you're an independent company that simply does one thing, which is you're developing a model, a foundational model, I think people are still searching for how they generate revenue from it. But don't forget, we run a cloud computing business and it's the perfect match between a large language model and cloud computing because the usage of the model creates demand for cloud. Our Quen model is both an open source model, but you can also use it through an API.
So if you use it through an API, we call it a model as a service. And the underlying demand for compute as you use the API is there. And we make money on cloud computing.
The logic is the same as why Microsoft has such a close relationship with open AI. When people use it, when you all have your chat GPT app on your phone, when you're using it, the underlying compute is provided by Microsoft. And of course, open AI is trying to diversify their source of compute now to other things like Stargate and things like that.
But but that's the logic. That's the business logic behind having both a foundational model that is very competitive and also cloud. And then with the more sophisticated user base, they will take our open source model and then they have their own data.
They want to train, post train their models with their data. In that case, we also provide a lot of cloud services, not just compute, but machine learning frameworks, data management, model testing tools and all those tools we provide them. And that all generates revenue for our cloud computing service.
So to which areas of AI do you think will generate the most value over time? The first place the value is, that's why Microsoft is worth so much with their cloud business. In the first place, they're kind of the beneficiary of AI, even though they're not doing AI themselves.
They have to rely on open AI. I think that's the first place. So the cloud players, it's just like you're selling picks and shovels when everybody is digging for gold.
The cloud players definitely benefit. But I think over time, there are a few areas. We already see the benefits of productivity within enterprises when we use generative AI.
So that's one area. The second thing is, I think, in over time with consumer Internet and also with the proliferation of agents, the consumer Internet sector is going to benefit because AI will change the way people obtain information and also engage with the interface. Maybe in the future, you will have different ways of engaging with the Internet other than through an app.
And that's going to be very exciting for the future. The third area of value creation is in the professional services. I'd have to say bankers, lawyers, doctors will have to learn how to deal with AI rather than being replaced.
They have to learn how to use AI to enhance their services. I think those are the areas where a lot of value is going to be probably destroyed partially, but also a lot of incremental value will be created. Yeah, makes sense.
And then, of course, one of the big moments was the deep sea moment. Capital efficiency, big, big question. You've been a little bit cautious about the spent on AI.
And I'm just curious, with the CapEx numbers still going up, what is your latest view on CapEx spent or overspent in your view? Well, I made a very simple observation. If you look at every hyperscaler, they're spending somewhere between 60 to 80 billion dollars on CapEx every year.
You know, so that's approaching like 500 billion dollars a year. And then you have people announcing new projects like Stargate is another 500 billion dollars. And so I so I made the comment, you know, look, I have to say, first, I'm very bullish on AI.
I'm very bullish on the infrastructure build out. But I was simply making an observation that it's not productive to announce these big hundred billion dollar type numbers, especially if you're doing it to please politicians. And then I had a conversation with some of the data center developers and they started to tell me that, you know, these are not technology guys.
These are real estate players. They started to tell me that they're building data centers without a off-take contract. And then I started to question myself.
If you start to build things on spec, just like in real estate, you may be approaching some kind of a bubble. That was kind of the comment I made. But I think there are real forces driving this demand for AI.
We all see it. We all experience it every day. I don't question the money that's being spent by the hyperscalers.
These are rational players. The Googles, Amazon, Microsoft, even Elon Musk, these are rational players. But as investors, you have to watch every quarter what they're spending very closely, whether the trend is still moving up or coming down.
I think that's going to be an important thing to look at. And the deep-seek moment itself, what are your thoughts on this? Certainly a wake-up call for US AI, but maybe even more so for open source.
Curious on your view. I think the biggest consequence or what does it mean to have a deep-seek moment is the value of open source, the way open source can help proliferate applications of AI. Because with open source, anybody, you don't have to be Sam Altman or Elon Musk or the Google guys, everybody can take the open source models and deploy it on their own infrastructure.
They can do it in a data center. They can download it into their notebook computer and then they could build on top of it. I think that will really help to proliferate the application of AI and deep-seek has demonstrated the value of it.
And they've also demonstrated through published papers how they can be more efficient in pre-training and post-training. And that's great. It'll benefit society.
And if they look maybe just more broadening out or what AI may mean for Alibaba, I'm curious, are there areas of investments that you feel you're doing, but they may not be appreciated by investors yet? We're one of the few companies that's vertically integrated from the model to the infrastructure. And I still say it, I think in this market, Google is one of those players.
They have Gemini, but they also run Google Cloud. I think that integration, that vertical integration of the value that the model is generating, which you could capture with cloud computing service and with the advancement in cloud and the expertise and infrastructure, you can optimize your system to run the AI better. This symbiotic relationship is something that investors probably haven't appreciated yet.
And I want you to know Alibaba is one of those players that have both. Yeah, that was one of the points in our white paper as well, that we think that we're going to see more vertical integration over time and that that is the best strategic positioning. Yeah.
I agree with that. If you look at Microsoft, you know, you look at open source, open, sorry, open AI, they're looking at ways to find, diversify their infrastructure needs with other players. And Microsoft wants to develop their own AI model.
So they've higher expertise into their organization to do both. So that's where the industry is moving forward. And maybe one other, so one other passion apart from AI that you have is sports.
I'm curious, you've invested in quite a few teams in basketball, you've invested in lacrosse, in football, both American and European. Right. What fascinates you about sports and especially what's your investment thesis?
Yeah. Investing into teams. Well, I've been playing sports since I was young.
So I would say I'm somewhat of a young athlete and I played American football in high school. And then I played lacrosse. I got cut from the baseball team for some reason, but also didn't make the swimming team.
So I was good at certain things. And also, I believe that sports really teaches you about life, about some of the values that I take from sports. Yesterday, I was at an event, you know, I had to make a speech and I told people my life philosophy is that I rather make assists than going for that basket myself.
I think enabling other people and assisting is to me is more fulfilling than being the star, scoring the goal or scoring the basket. So I learned a lot of values of life that I take away from sports and I teach all my kids to not only play sports, but also learn about life through sports. One of the biggest lessons in sports is you will not have a perfect winning record.
Every season you're going to lose games. And so if you lose, how do you bounce back from adversity? And that's it really applies in a startup business or in a business where we're 26 years old, you know, because you're going to have ups and downs.
You're going to have huge setbacks. If you look at Alibaba over the last five years, we had gigantic setbacks from competition, from regulation, from geopolitics. But you have to be able to figure out how you recover from falling to the ground.
My my first principle and my only principle investing in professional sports is that I want to be involved in leagues where the best players in the world play. The NBA is where the best players play. About a quarter of the NBA's player pool are non-American and everybody comes to the U.S. to play in the NBA.
You know, in in American football, well, that's the only the NFL is really the only place where where you can play. And lacrosse, I, you know, I still lacrosse is such a niche sport. It's a poor sport in the sense that there's no money in it.
Every owner of a lacrosse team loses money. But I was just amazed, you know, the other night I was at in San Diego. We play in this 60 year old building.
It's like almost falling down. Like the asbestos risk is very, very high. It's called Pachanga Arena and in this dilapidated building, but we had an incredible fan base.
And who are the players? There's Westberg, one of the best Canadian players, there's Jeff T, the top, that's probably the best lacrosse players in the world. Trevor Baptiste, the best faceoff guy in the world playing in the 60 year old building.
So but they are the best players. I mean, you would know a little bit of lacrosse. You recognize those names.
But I just think that you you got to bet on the talent where the best players play. And so that's a good second to asking you about investing in women's sports. Yeah, you were early in investing in women's sports in 1990, sorry, in 2019, right?
You bought the New York Liberty. So curious, at that point, I think they were at the bottom of the league, if I'm not mistaken, or close to the bottom. We had something like a 2 and 30 record.
We won two games the whole season. And you stepped in and you took ownership of the team. What prompted that decision?
It was simply a very simple sort of, well, we have a men's team, so the opportunity that became available to buy a women's team, why not? It was sort of the symmetry of the beauty of the symmetry. I have kids.
I have three kids. I have a daughter and two sons. I would just teach as equally teach my daughter how to play lacrosse as I teach my son.
So why not? Why not have both? Right.
And and it was that simple. It wasn't because, you know, now with revisionist history, you could say, well, I saw this thing going up. But if you have the men's team, why not have a women's team?
It's there should be equal. There should be equal treatment. It was that simple.
And then congratulations. Last season you won. So from second to last to first in a matter of five years.
A matter of five years. Yeah. Congratulations.
And a great kickoff on Saturday again. Yes. We had our home opener, which also is the ring ceremony where we celebrated the championship from the past season.
And we got every all the players rings, championship rings. They're gigantic. You know, you wouldn't wear every day, but everybody loved the ring.
And we opened with a big win against the Las Vegas Aces, which is a very strong team. And our team looked very good. So I'm very encouraged by the good start.
Well, we're going to be rooting for you. One of the questions that I would be remiss not to ask at UBS is our motto is thinking is our craft. So craft is something that's very important to us as a concept.
I'm curious whether it's sports or business. What does craft mean for you? Craft means something, a skill set that you develop where you are in the top one percent of the population.
You're better than 99 percent of everybody else. I think that's what what it means to me. So you have to work at it and spend time.
It's developed over time. You know, the best athletes hone their craft through repetition, that muscle memory. Right.
So you're it involves both talent. But more importantly, it's perseverance. You have to work harder than everybody else in where it's developed that craft.
I think that's what it means to me. And then a last question. We as CIO have this thesis that any investment right now, you have to evaluate through the AI lens.
So AI is your potential main competitor. And again, with sports, I'm wondering, what is your investment thesis there? And could it be that sports is really one of the few, maybe only areas of entertainment that ultimately is going to be immune to the threat from AI?
Yeah. So on the one hand, I think AI is never going to replace athletes. We still want to see real human beings perform and compete against each other.
So that's immune, I think. Yeah. Otherwise, it wouldn't make sense to have humans compete against robots.
But everything else can be disrupted and changed for the better by AI, how you present the games, how you analyze from for competitive reasons, how you you know, we already use computer vision cameras to to track player movements. So the kind of statistics that you can track is not just baskets and assists and turnovers. It's whether you've made that basket through a contested defense or not.
And with great camera work and computer vision, you can track statistics in a much closer way. And that's going to really propel kind of the next advancement in sports. The way you're presenting the game itself, you can do a multitask of multicast of screens of the traditional broadcast, but have a separate broadcast that's enhanced by AI, you know, for fun.
It's sort of watching a video game. So there's a lot of things that you can do to to really up the game on the fan experience. So so what you were saying is really AI enhancing something that is a truly human experience as opposed to replacing it.
Yeah, I do have this philosophy about sort of human versus machines. First of all, you know, people say artificial intelligence. What does artificial mean?
It means that the machine is trying to mimic human beings, try to approximate what humans do. But I think there's going to be diminishing returns on trying to exactly mimic a human being. There's like if I want to, you know, socialize or even if I want to have someone come clean my home, I think it would be very weird to have a robot that looks just like a human being.
It's kind of creepy. If I want someone, something to vacuum my floor, it can just look like a vacuum cleaner. It doesn't have to be a humanoid robot.
There are certain things where you still want to interact with real human beings. I think that's just the way human beings are. So I would say in the future, people shouldn't call this artificial intelligence.
People should just call it machine intelligence as opposed to human intelligence. I think to the question of AGI, whether AI will be smarter than human beings, I think in in a certain sense, of course, AI can compute faster, do math or code faster. But that's that's the intellect aspect of your brain.
But the intelligence aspect of your brain, which involves EQ, emotions, desires, love and all those aspects, how does how does a machine replicate that? And and and when you look when you think about training AI models as an analogy of parents raising children. How many interactions do you have with your kids that has that will never be captured in the training data?
It would be very disruptive if they try to capture every interaction that parents have or between husband and wife or, you know, that it's. It'll never happen, I think. That's my that's my view.
But of course, there's a lot of people that will disagree with me and they're all smarter than I am in the intellect sense, but not in the intelligence sense. I think this couldn't be a better closing statement, Joe, so thank you so much. It's an honor.
To our listeners and clients, thank you for your time and engagement. If you have enjoyed this episode, you may subscribe to UBS Market Moves, available on Apple podcasts and Spotify for additional content. Until next time, where again, we decode the future of AI layer by layer.
UBS chief investment offices, investment views are prepared and published by the Global Wealth Management Business of UBS AG or its affiliates. The views and opinions expressed in this material by external guest speakers are those of the author speaker and are not those of UBS, its subsidiaries or affiliates. Accordingly, UBS does not accept any liability over the content of this material or any claims, losses or damages arising from the use or reliance of all or any part thereof.
This material has no regard to the specific investment objectives, financial situation or particular needs of any specific recipient and is published for informational purposes only. For a full legal disclaimer applicable to the independent investment views produced by UBS, please visit our website at UBS dot com forward slash CIO dash disclaimer.