Who Profits from AI? The Expectations and Pitfalls for "Shovel-Selling Companies"

"Which AI will win next?" Every time a new model is announced, we feel the urge to compare its performance and usability. However, observing this competition from a different perspective reveals another key player.

The semiconductors that power AI. The equipment that manufactures those semiconductors. The networks that transport data. The servers that handle computation, supported by power and cooling facilities.

Regardless of which service gains popularity, there are physical facilities behind the screen. AI is both digital intelligence and a major infrastructure industry.

On September 26, 2026, an article in DER AKTIONÄR published by Germany's Aktiencheck introduced this structure with the metaphor "companies making the shovels for the AI revolution."

However, if this metaphor is interpreted as "buying backstage companies guarantees profit," one might overlook the crucial aspects.

What does "selling shovels" mean?

In the gold rush, opportunities arose not only for those searching for gold but also for businesses supplying tools. Applied to AI, instead of predicting which service will ultimately become popular, the focus is on the demand for equipment and components necessary for development and operation.

The original article highlights four roles: semiconductor manufacturing equipment, dedicated AI chips and networks, systems for data centers, and memory. The explanation is that companies supplying multiple customers and markets are less likely to be affected by the success or failure of a single AI model.

It's important to note that the article also serves as an introduction to a paid investment report. In the public section, the names of the four target companies are not disclosed, and warrants touting potential price increases are also introduced.

Therefore, what can be confirmed from this article is the framework of the investment theme, not enough information to verify the specific competitiveness or future profits of the four companies. This article will not attempt to speculate on the company names.

Considering AI's backside through four jobs

This structure is easier to understand when divided by role.

※Based on the four fields from the original article, this article organizes roles and points to confirm.

What becomes apparent is that the term "AI-related" alone cannot fully explain how companies earn.

The situations requiring computational power and those requiring fast data transport differ. The cost structure and pricing power also differ between companies selling components and those responsible for assembly.

Even with the same tailwind, the growth in sales and the profits retained may not be the same.

The "off-screen constraints" of power

One piece of evidence showing the importance of facilities supporting AI is power demand.

The International Energy Agency (IEA) in its 2025 report "Energy and AI" estimated the power consumption of global data centers to be about 415 TWh in 2024, with a basic scenario projecting an increase to about 945 TWh by 2030.

This is not the consumption solely by AI but the overall figure for data centers. While IEA cites AI as a major factor for the increase, other digital services are also included. Furthermore, the 2030 figure is a future projection and not a confirmed demand.

The same report also pointed out that without addressing issues like the power grid, about 20% of planned data center projects face the risk of delays.

Even if there is demand for facilities, they may not be operational as planned. In this sense, power supply is both a condition supporting the growth of the AI industry and a condition that can limit growth speed.

On social media, "backstage is the real deal" and "backstage is also risky" intersect

This investment theme is also discussed on overseas bulletin board-type social media, Reddit.

What is introduced here is not a direct response to the original article but a summary of related posts and comments about AI infrastructure investment. It is a part of the opinions that could be confirmed and does not represent the view of the entire market.

In the thread "Ai bubble who wins?", the poster expressed an expectation for the infrastructure supporting AI companies rather than the AI companies themselves. They particularly focused on power grids and cooling facilities, emphasizing the essential foundation over trends.

On the other hand, there were concerns in the comments about whether excessive capital investment might lead to lower service prices, making it difficult to recoup the invested capital. There were also points raised about the impact on supply companies if major customers reduced AI investments.

Furthermore, in response to opinions assuming the internalization of related facilities by large tech companies, there was a counterargument that the design and manufacturing know-how accumulated by specialized manufacturers cannot be easily replicated.

The crux of the debate is not just "whether facilities are necessary" but "who can supply the necessary facilities and at what profit margin."

The distance between "necessary regardless of who wins" and "profitable regardless of who wins"

The appeal of the explanation of shovel companies is that it seems one does not need to predict the detailed outcomes of AI service competitions.

However, having a small dependency on a specific model and having a small dependency on the overall AI boom are different matters.

For example, even if a company has multiple customers, if those customers increase data center investments at the same time and reduce them at the same time, the demand waves overlap. The number of customers alone does not suffice to determine adequate diversification.

Moreover, even if the overall market size of the industry grows, price reductions due to competition or the costs of increased production could squeeze profits. Equipment invested in to capture demand might later become excessive.

Furthermore, even if a company's profits grow, if that growth is already largely factored into the stock price, shareholder returns may yield different results.

The proliferation of AI, the increase in profits for supply companies, and the profits investors gain are interconnected but not the same event.

To assess growth, understanding the circumstances of those purchasing the equipment is also necessary

In deciphering this structure, it's helpful to look not just at the supply side but also at the paying side.

Why do companies purchasing equipment increase computational power? Is it to increase sales by providing services to customers, to reduce internal operational costs, or to prepare for future competition?

Investment can occur for any purpose. However, the conditions for continued expenditure differ.

If companies are making upfront investments anticipating future growth, it becomes crucial whether usage and revenue catch up later. Even for supply companies with increasing orders, it's necessary to separately consider whether customers can repeat orders of the same scale.

To advance beyond the explanation of "growing because it's AI," it's essential to connect the expectations of sellers with the profitability of buyers.

The main players in the AI revolution might not appear on the screen

When we use AI, what we see are responses, images, and convenient interfaces. However, what makes that experience possible is the accumulation of diligent work involving machines, components, wiring, and power.

The metaphor of "shovels" in the original article is useful in directing attention there. It serves as an entry point to perceive the competition surrounding AI beyond just service names or model performance.

However, there is competition even in the business of selling tools, and customers' wallets have limits. Being backstage does not inherently guarantee revenue or stock price.

When reading about the AI gold rush, the question is not just who is the most prominent. It's about who is handling the indispensable work and who continues to pay for that value. This question brings the glamorous growth narrative back to the reality of business.

Source URL

1. Aktiencheck／DER AKTIONÄR "Die Schaufelbauer der KI-Revolution" (September 26, 2026)
   The starting point of this article. An article introducing the four fields supporting AI infrastructure.
   https://www.aktiencheck.de/news/Artikel-Schaufelbauer_KI_Revolution-20124773

2. IEA "Energy and AI" Executive summary (2025)
   Source of data center power consumption, 2030 demand forecast, and delay risk due to power grid constraints.
   https://www.iea.org/reports/energy-and-ai/executive-summary

3. Reddit r/stocks "Ai bubble who wins?"
   Summary of SNS discussions on AI infrastructure investment. Opinions on power grid and cooling expectations, investment recovery, dependence on major customers, and in-house production versus specialized manufacturers' technical skills. Not a direct response to the original article, nor adopted as fact for individual stock information or forecasts in the post.
   https://www.reddit.com/r/stocks/comments/1q2amz4/ai_bubble_who_wins/