Expeditors International of Washington, Inc. Status update

Morning everyone, and welcome to our webinar today. My name is Olivia Tan, and I am a Senior Geopolitical Analyst at Onyx. We offer a different webinar topic each month, and this time we will provide our AI outlook. The AI boom has led to a physical build-out of chips, servers, data centers, and power infrastructure globally. The speed and scale of this hardware build-out is actively reshaping supply chains and logistics strategies. Join our analysts today as we assess the impacts of the AI boom to air and ocean freight markets, shipping lanes, and discuss the longevity of this build-out. Before we begin, we've seen a lot of interest in the application of AI to logistics operations, notably in shipment visibility and service improvements.

However, in this webinar, we'll focus instead on the impact of the AI investment boom on freight markets and supply chains. Before we begin with the content, there are just a few administrative details to cover. We will have about 45 minutes of content to share, and we will save the last 15 minutes for the Q&A session. Please submit your questions in the Q&A box, and we will do our best to address your questions during our Q&A session. A copy of the presentation, notably the slides, will also be available later. To receive a copy of the presentation, please fill out the brief survey that'll be emailed to you shortly after this webinar. Please visit our website as well and subscribe to receive information on Onyx's future webinar.

We would also like to invite you to explore our latest insights on LinkedIn and the Vantage Point blog, which features a mix of short updates and in-depth articles. Please use the QR codes at the top to follow us either on LinkedIn or to subscribe to our Vantage Point blog. For those of you who are not familiar with Onyx, just to do a quick introduction. Onyx is a consulting division of Expeditors, and we help clients build more efficient and resilient supply chains. We are uniquely positioned to help our clients in identifying geopolitical, regulatory, economic, and operational disruptors, which can then be translated into a more forward-looking end supply chain. All of these are done through advisory engagements and in projects are also tailored to individual client needs, either as one-off projects or ongoing retainers. These are Onyx's services lines.

In a nutshell, our service offerings cover various areas within the supply chain, like planning and strategy, trade and compliance, sourcing, and manufacturing. Please contact us if you have a project or need where our advisory expertise can assist. Onto our speakers today. I'm excited to introduce the speakers who will be presenting today, myself, Adam Carson, and Surya Nugroho. I'm a Senior Geopolitical Analyst in Onyx, and I work primarily on the Indo-Pacific. I hold honors degrees in history, international political economy, and my work has been featured in The Pacific Forum, the Asia Times, and other media outlets. Surya Nugroho is a seasoned policy expert with 14 years of experience across geopolitics, policy analysis, and supply chain management. He currently serves as Onyx's Senior Geopolitical Analyst, leading the firm's Southeast Asia coverage. Onto Adam Carson. Adam has more than 20 years of experience as an economic advisor to global leaders across a range of industries.

He has extensive experience in the U.S., Europe, and Middle East. Adam most recently worked at Chevron as a Senior Economist and is responsible for Onyx's macroeconomic analysis and forecasting. With that, I think we will cover one more slide on our content today in the webinar. What we will cover in the next 45 minutes or so, with 15 minutes for Q&A, is the current state where the AI build-out stands in terms of capital, supply, and delivery. We will cover hyperscaler CapEx plans through 2023. We will look at data center power demand as it relates to infrastructure and then the supply chain and critical minerals for the AI supply chain.

Adam will cover our possible future trajectories, bringing you through three scenarios of AI development moving forward: a fast build scenario, a slow build scenario, and a pullback. Lastly, he will touch on what it means for freight and what to watch. With that, I will hand it over to Surya to kick us off.

Thanks, Surya. Thanks a lot, Olivia, for the kind introduction.

Good morning, everyone. As Olivia has mentioned before, we will start by basically providing you with our analysis as well as insights on the current state of AI development. Where are we going with AI? What is the state of play of AI currently? There are four elements that we want to cover here. First one is about capital. Capital is readily available around big five data AI CapEx projected to exceed $1 trillion by 2029. Then the revenue is scaling as these AI companies have already started to also offer enterprise AI functions. The revenue for them is scaling up as well. In terms of economic impact, the economic impact is significant, especially for the U.S. economy.

AI contributes around 1.5%-2% of the U.S. gross domestic product, as well as 50% of the growth net imports. Supply chains are heavily concentrated, and it benefits a handful of countries. We are talking about Taiwan, South Korea, China, and Mexico carrying the value chain. There is one thing or one risk that you all need to monitor. We will discuss this in the second part, and Adam will talk about this later on in more in-depth. There is delivery flagging from two different sides. The first one is on the power supply or energy supply construction. Right now it is only about 5 gigawatts of the roughly 16 gigawatts of U.S. capacity announced for 2026, as well as we are talking about components and equipment as well.

There are a couple of bottlenecks emerging in the AI supply chain, namely, high-bandwidth memory, chips bottlenecks as well. We are also seeing that packaging is also starting to experience a bottleneck as well. Moving on to reporting and progress, I will give a bit more detail about the CapEx plans, the first part. Hyperscaler, the CapEx plans will grow by about 28% per annum from 2025 to 2030 after a tremendous growth of CapEx growth from 2020 to 2025, around 114%. Most of the CapEx will go to inference. Why inference is so important here? Because right now AI is at the phase of implementation, so now more and more people are using AI. The cost of inference is really high. We are talking about because of the scale. Inference happens millions of billions of times, depending on the use.

Because of that, they need more data center. Hence, you can see the figure on the top, that CapEx on data center is also increasing tremendously, because they need data center, more and more data center to do inference. To do a better inference, we are talking about speed as well. Instantaneous responses, which require advanced and basically power-hungry GPU. The more investments are needed to basically acquire a more advanced GPU for doing a better inference. Complexity, as the model becomes more advanced and can solve complex tasks, it requires more computational resources, which led to more data centers, as I said before, need to be built. With that comes with a rising cost of energy, as well as the wear and tear of the hardware, in this case, the GPU. You see that the CapEx plans is really high.

It is tremendous. For that, basically for the AI companies to justify the CapEx plans, they need to get high margins as well as sustained traffic growth. We anonymize the company here, but this company A, B, C, and so on and so forth, represents the top AI firms globally. When you talk about, I think the most important graph here is the one on the right side. We are talking about the revenue growth required to break even NPV. There is one firm, more specifically Company B, that relies on frugality to generate positive ROI. Company B, basically, they need a lower revenue growth to basically make a break even point, to reach break even point. Meaning that they spend more efficiently compared to the others. It is a different strategy.

The other strategy is basically Company A, C, and D, they rely more on the strong revenue streams. But they spend more on the infrastructure, they spend more on the data centers, and that is why they require a stronger revenue growth in order for them to justify their CapEx. Moving on to the AI, the supply chain mapping. As I have already said before, the AI supply chain is heavily concentrated in a handful of countries, more specifically here, in five countries. Number one is, the first one is Taiwan. We are talking about chips, the leading-edge logic and advanced packaging. 90% of the sub-5nm of logic output is produced in Taiwan by one company, TSMC. Netherlands, because ASML is headquartered in Netherlands, and they are the only supplier of EUV lithography at the moment.

For the EUV lithography, it is pretty much concentrated in this one company. In Japan, about 50% of global silicon wafers is produced in Japan. We are talking about photoresist and substrate film as well. In South Korea, we are talking about high-bandwidth memory. There are only three companies that manufacture high-bandwidth memory, right? One based in the U.S., Micron Technology, and the other two, SK Hynix and Samsung, are based in Korea or Korean companies. Clearly, the high-bandwidth memory is pretty much concentrated in South Korea. I think we cannot leave China out of it because China basically dominates critical minerals refinery. About 99% of primary gallium refining is done in China. Also, a couple of different wafers as well. We are talking about germanium, tungsten.