Samsung in the AI race: Record profits do not guarantee victory

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Samsung in the AI race

Samsung benefits from the AI boom

Samsung Electronics has released preliminary financial results for the third quarter of 2026. The company’s operating profit reached $80.1 billion, nearly nine times higher than a year earlier. Revenue rose 127% to $145.5 billion, according to CNBC.

The main driver of growth was demand for memory chips used in artificial intelligence. These components are used in data centers that run AI models. High-bandwidth memory, or HBM, is particularly important because it is installed alongside graphics processors made by Nvidia and other AI accelerator manufacturers. It enables the rapid transfer of the huge volumes of data needed to train and run neural networks.

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The second quarter was also a record period for Samsung. Revenue reached about $128 billion, while operating profit stood at $66.8 billion. That means the company increased operating profit by roughly $13.3 billion in just one quarter.

However, even these results fell short of analysts’ expectations. After the preliminary report was released, Samsung shares fell by more than 2% on the Seoul stock exchange. Investors had expected even stronger figures amid massive spending by technology companies on AI infrastructure.

Results for Samsung’s individual business divisions are not yet available. The company plans to publish its full financial report, including a breakdown by division, on October 29.

Samsung is catching up with rivals

Despite record profits, Samsung still trails competitors in advanced memory chips for AI. Its main rival is South Korea’s SK Hynix, which moved earlier to establish mass HBM shipments for Nvidia accelerators. U.S.-based Micron is also expanding production and competing for contracts with the world’s largest technology companies.

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Samsung hopes to close the gap with next-generation HBM4 memory. Citigroup analysts expect prices for 12-layer HBM4 chips to rise by 100–150% in 2027. The company is also expanding production capacity to increase output and secure more orders from AI hardware developers.

In September, Samsung announced a strategic partnership with French AI developer Mistral AI. Its models are expected to be deployed across Samsung facilities, including semiconductor production. AI is intended to help automate manufacturing processes and handle internal engineering tasks.

From servers to smartphones

Another part of Samsung’s strategy is to put AI directly into devices used by hundreds of millions of people. The company can leverage the scale of its smartphone, television and home appliance businesses rather than relying only on component sales to data centers.

Galaxy AI plays a central role in smartphones. On compatible devices, artificial intelligence can translate phone calls, transcribe audio recordings, edit photos and search for information using images. Some functions run directly on the device, while others require an internet connection.

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Samsung also uses AI in home appliances to automate everyday tasks. Washing machines, for example, can adjust washing settings based on the load, while refrigerators equipped with cameras can recognize certain foods and help create shopping lists. In televisions, AI is used to improve picture and sound quality.

In July, Samsung management said the number of devices with Galaxy AI should reach 800 million by the end of 2026. The company also expanded AI agent capabilities in the Galaxy S26 lineup. In addition to its own Bixby assistant, users can access Google Gemini and Perplexity to search for information, manage settings and perform actions inside apps.

What will decide the race

Record profits show that Samsung is already benefiting from the AI boom, but the race itself is still gaining momentum. The next stage will depend on whether the company can turn growing demand for memory into a sustainable position in the market for next-generation chips.

At the same time, Samsung is competing on two fronts. It sells components for AI infrastructure while also integrating artificial intelligence into its own devices. If both businesses begin delivering significant returns at the same time, the company could gain an advantage that chipmakers focused only on components do not have.

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