Data as Currency in the AI Era: How Samsung Electronics, Aspermont and Siemens Stand to Benefit

Samsung Electronics: Acceleration Through AI

Samsung Electronics is known for its consumer business, which includes smartphones, OLED displays, and home appliances. But the South Korean conglomerate really makes its money with its highly profitable semiconductor division. Thanks to the chip business, revenue rose by about 28% in the second quarter to the equivalent of approximately USD 119 billion. Net income even reached a record USD 49.8 billion, representing a 52% increase. This trend shows no signs of slowing down anytime soon. Demand for DRAM and NAND memory is being driven by the expansion of AI server infrastructure, while price increases are also being implemented.

But Samsung is looking ahead and wants to leverage AI for its own benefit. The company must stay ahead of the curve to survive the fierce competition. The collaboration with Anthropic demonstrates how this can be achieved. In developing custom chips, Samsung has leveraged its partner's capabilities. Part of this work involves time-consuming verification and modeling of chip designs. According to reports, Samsung's chip division is relying on the AI tool Claude Code directly in the development of system-on-chips. The gains in productivity can certainly be described as enormous. Previously, simply setting up the virtual test environment and testing nested data paths for a customer's chip design regularly took more than 30 days. With Claude Code, the process could be completed within 2 days.

With such advances, Samsung aims to gain an edge over the competition. And the company certainly needs this efficiency, as its main competitor, Qualcomm, employs around 52,000 people worldwide, while Samsung employs only 6,000 in its chip division. Samsung Electronics' share price multiplied from early 2025 through the spring of this year. A consolidation is currently underway. Investors who want to be in the chip race should definitely bet on Samsung.

Aspermont: Entering the AI Era with Real Data

In 2024, one of the most well-known research papers on artificial intelligence was published in Nature. According to the paper (Shumailov et al.), the authors demonstrated mathematically and empirically that, without countermeasures, generative AI models become unusable after several generations of purely synthetic training data and produce distorted or meaningless results. The fact that this is already part of reality is evident in many online texts. AI learns from other AI-generated texts; ultimately, it reproduces an extremely smoothed-out, statistical probability of language.

Therefore, the present and future value of AI lies primarily in real data. Industrial companies such as Siemens or Samsung Electronics are already building the artificial intelligence they use on real data and do not rely on free material from the internet. Those who possess real data can successfully shape the age of artificial intelligence.

Aspermont could also be among the winners of these developments. The Australian media company specializes in trade publications and possesses a treasure trove of data for the mining industry. The goal is to transform the traditional publishing business into a highly profitable Data-as-a-Service (DaaS) model for the commodities sector. A prime example of this is the collaboration between Aspermont and Rio Tinto, one of the world's largest mining companies. The two partners are basing their collaboration on digitalization and training AI with the data. Aspermont possesses a media archive dating back over 180 years, containing specialized information, historical reports, and technical analyses from the sector. This data is processed and structured via platforms such as Mining IQ. It is also supplemented with data from third-party providers.

For Rio Tinto, this collaboration could prove to be extremely lucrative. It can be used for market analysis, technology research, and strategic decision-making. Aspermont, in turn, benefits as a provider of data licensing deals and digitization contracts. Thus, Data-as-a-Service could be the key to Aspermont's future.

In the coming quarters, this approach could demonstrate the transformation of the company's revenue model. On the stock market, Aspermont is valued at just AUD 12 million. Analysts at GBC Research see enormous potential here. In the long term, the company could achieve an EBITDA margin of 20%. The target price is AUD 5.20, which is a multiple of the current share price.

Siemens: Near All-Time High

Siemens is the world's largest industrial software company for manufacturing automation and digital twins. The DAX-listed company is a leader in industrial automation, particularly in control software and programmable logic controllers. Depending on the region, Siemens likely holds an estimated market share of 30 to 40%, though for historical reasons, it is strongest in Europe. The focus is primarily on top automakers, aircraft manufacturers, and electronics conglomerates.

As a result, Siemens possesses one of the industry's largest data treasures. And the Munich-based company is putting this power to good use. It links its broad physical infrastructure in factories with the virtual software world (digital twins, CAD/PLM) to create so-called "industrial AI solutions". Siemens builds AI models here that are based on specific operational and real-time data. This can significantly boost efficiency. For example, this enables "predictive maintenance". Using digital twins of factories, Siemens can simulate products, production lines, and entire plants in the virtual world. This eliminates the time-consuming and expensive construction of physical prototypes, can optimize energy systems, and allows for the simulation of capacity utilization in advance. A prominent example is a collaboration with Schaeffler, where automation code for robots and production lines can be created in a fraction of the time.

Building on this wealth of data, Siemens could become one of the major industrial winners of the AI revolution in the coming years. Evidently, many investors believe this as well. The stock of Germany's most valuable company has been rising steadily since 2022 and is currently near its all-time high. However, due to the enormous price appreciation, the dividend yield has now fallen to around 2%. Long-term investors can use corrections as an opportunity to buy in.

Samsung is accelerating its development cycles with modern AI, enabling it to keep pace with the competition. Aspermont is leveraging its massive mining database and aims to win over customers, partners, and investors with its "Data-as-a-Service" approach. Siemens, in turn, is using its industrial data to help customers operate more efficiently.