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Introduction: The World Is Running Out of the Chips Powering Artificial Intelligence
The global race to build artificial intelligence infrastructure is creating a new reality for the semiconductor industry: demand is rising faster than advanced memory capacity can be expanded. As technology companies invest billions of dollars in data centres, AI accelerators, cloud platforms, and large-scale computing systems, the pressure on memory-chip suppliers is becoming increasingly intense.
Samsung Electronics, the world’s largest memory-chip manufacturer, now believes the supply imbalance could persist far longer than many investors expected. The South Korean technology giant has warned that global chip shortages may become more severe and continue into 2028, while revealing that it has secured long-term supply agreements with some of the world’s largest data-centre operators.
The company’s latest financial results show how dramatically the AI boom has transformed the semiconductor market. Samsung reported an extraordinary increase in chip profits, but the same rise in memory prices that strengthened its semiconductor business also damaged its mobile division. The company is benefiting from the shortage while simultaneously experiencing the costs of operating inside it.
Samsung’s results therefore tell a larger story about the future of the technology industry. AI is creating enormous opportunities for chip manufacturers, but it is also increasing costs, concentrating supply, changing contract structures, and forcing major technology companies to reconsider how they secure the computing resources required for future growth.
Main Summary: Samsung Moves to Lock In AI Demand for Years
Samsung Electronics reported that its semiconductor division generated operating profit of approximately 89.2 trillion won, or around $61.7 billion, during the second quarter. The result represented a more than 250-fold increase compared with the same period a year earlier and helped push the company’s total operating profit to approximately 89.5 trillion won.
The company’s overall revenue climbed roughly 130% to 171.5 trillion won, reflecting the powerful impact of rising memory prices and growing demand for AI-related hardware.
Samsung also revealed that it has signed supply agreements with the five largest global data-centre companies and is approaching similar agreements with another five major customers. Although the company did not identify the firms, the announcement highlights the scale of long-term demand emerging from the world’s largest cloud and AI infrastructure operators.
According to Samsung, many customers are now requesting multi-year supply arrangements rather than relying on short-term purchases. The company aims to secure long-term contracts covering approximately two-thirds of its memory production, with some agreements expected to last at least five years.
These contracts may include upfront payments and minimum pricing provisions. Such terms could protect Samsung from the financial risks associated with building expensive semiconductor factories while giving customers greater certainty that they will receive critical memory products during a prolonged shortage.
The AI Infrastructure Race Is Changing the Semiconductor Industry
Artificial intelligence systems require far more computing power than conventional applications. Training and operating large AI models depend on massive clusters of advanced processors, high-speed networking equipment, storage systems, and specialised memory technologies.
High-bandwidth memory, commonly known as HBM, has become particularly important because it allows AI processors to access large amounts of data at extremely high speeds. Advanced AI accelerators from companies such as Nvidia and AMD depend heavily on HBM to deliver the performance required by modern generative AI workloads.
As more technology companies build AI data centres, demand is increasing not only for AI processors but also for the memory products surrounding them. This creates a supply challenge because advanced memory cannot be produced instantly. New manufacturing capacity requires years of planning, billions of dollars in investment, highly specialised equipment, and complex production processes.
Samsung’s warning that shortages could extend into 2028 suggests that the industry may be entering a structural supply constraint rather than experiencing a short-lived market disruption.
Long-Term Contracts Could Reduce the Industry’s Boom-and-Bust Cycle
The memory-chip market has historically been highly cyclical. During periods of strong demand, manufacturers increase production and invest heavily in new factories. When demand weakens, excess inventory can cause prices and profits to fall rapidly.
Samsung’s move toward long-term supply agreements may represent an effort to reduce this volatility.
By securing contracts that extend for several years, Samsung could gain greater visibility into future demand. Upfront payments may help finance new production capacity, while minimum-price provisions could reduce the risk of investing billions of dollars only to face a sudden collapse in chip prices.
For customers, the agreements could provide greater certainty that critical memory products will remain available. This may be particularly valuable for hyperscale cloud companies that are planning AI infrastructure projects over several years.
The strategy could gradually transform memory chips from highly volatile commodities into strategically contracted infrastructure components.
Investors Remain Concerned Despite Samsung’s Record Results
Samsung’s strong earnings did not completely reassure investors. The company’s shares closed approximately 0.7% lower after rising as much as 8.4% during trading. Rival SK Hynix experienced a sharper decline, ending the session down approximately 5.6%.
The market reaction reflects growing concern about whether the enormous spending on AI infrastructure can continue at its current pace.
Major technology companies are investing heavily in data centres, AI processors, networking systems, and energy infrastructure. However, these investments require large amounts of capital before they generate meaningful returns.
Recent financial results from major technology companies have increased concerns that AI spending may pressure cash flow. Meta reported a significant decline in second-quarter free cash flow, while Alphabet reported a cash-flow-negative quarter.
Investors are now asking an important question: if AI infrastructure becomes increasingly expensive, how long can technology companies continue expanding their data-centre capacity at the current rate?
Samsung’s contracts suggest that major customers remain committed to long-term AI investment. However, the stock market is increasingly focused on whether those investments will eventually produce enough revenue to justify their cost.
Samsung’s Semiconductor Success Creates Pressure on Its Mobile Business
Samsung’s latest results also demonstrate how rising chip prices can create winners and losers inside the same company.
The semiconductor division benefited from higher memory prices and strong AI demand. At the same time, Samsung’s mobile business reported a quarterly loss of approximately 700 billion won, its first quarter in the red.
Higher memory costs can increase the expense of manufacturing smartphones and other consumer electronics. If companies are unable to pass those costs on to customers, profit margins can shrink.
This creates a complicated situation for Samsung. The company earns more by selling memory chips, but its device businesses may pay more to purchase the components needed for smartphones and other products.
The result is a growing dependence on the strength of the semiconductor division. If memory prices remain high, Samsung’s chip business could continue generating enormous profits. However, a future decline in memory prices could also have a larger impact on the group’s overall financial performance.
Samsung Gains Momentum in the High-Bandwidth Memory Market
Samsung’s earnings also indicate progress in its competition with SK Hynix for leadership in the HBM market.
HBM is one of the most strategically important semiconductor technologies in the AI era. It is used alongside advanced processors to improve data-transfer speeds and support demanding AI workloads.
Samsung counts Nvidia and AMD among its HBM customers and expects revenue from HBM4 products to more than triple during the third quarter.
The company believes this growth could allow its HBM market share to move closer to its position in the broader DRAM market during the second half of the year.
The expansion is significant because HBM products generally provide higher value than conventional memory chips. Winning major AI customers could therefore strengthen Samsung’s long-term profitability while improving its position in the rapidly growing AI hardware ecosystem.
The Foundry Business May Be Approaching a Recovery
Samsung also expects its semiconductor foundry business to improve as factory utilisation rates rise and chip prices strengthen.
The company’s foundry division competes with Taiwan Semiconductor Manufacturing Company, commonly known as TSMC, and with Intel’s expanding contract-manufacturing operations.
Samsung has invested heavily in advanced manufacturing technology and is preparing to expand its production footprint in the United States.
The company expects its Taylor, Texas semiconductor facility to begin operations this year. It also plans to begin construction on a second factory that could enter mass production around 2030.
These investments demonstrate the scale and long-term nature of the semiconductor race. Advanced chip factories are not short-term projects. They require years of construction, specialised equipment, skilled workers, and large amounts of electricity and water.
The factories being planned today may support AI systems that do not yet exist.
Samsung’s Cash Position Strengthens Expectations for Shareholder Returns
Samsung’s strong chip earnings helped increase its net cash position to approximately 167 trillion won by the end of June.
The company’s quarterly profit exceeded its combined earnings over the previous three years, increasing expectations that Samsung may expand shareholder returns.
Chief Financial Officer Park Soon-cheol said the company was actively discussing special dividends and other elements of its shareholder-return programme.
Samsung’s financial position also means that it has limited need to raise additional capital. Unlike some competitors, the company can use cash generated by its diversified businesses to support semiconductor investments.
Samsung has also said it is not currently considering issuing American depositary receipts in the United States, unlike SK Hynix, which recently entered the U.S. market through ADRs.
Deep Analysis: How a Long-Term Chip Shortage Could Affect Technology
AI Compute Demand Is Becoming a Supply-Chain Problem
The growth of AI is no longer limited by software development. Increasingly, it is constrained by physical infrastructure.
Every large AI system depends on processors, memory, networking equipment, power generation, cooling systems, data-centre space, and skilled engineering teams.
If memory shortages continue until 2028, technology companies may need to redesign infrastructure plans around limited hardware availability.
HBM Could Become a Strategic Bottleneck
HBM production is technically complex and depends on advanced packaging and manufacturing capacity.
A shortage in HBM could delay the deployment of AI servers even when AI processors are available.
The supply chain is therefore only as strong as its most constrained component.
Long-Term Contracts Could Reduce Spot-Market Volatility
Multi-year agreements may reduce uncertainty for both Samsung and its customers.
However, long-term contracts could also make it more difficult for smaller companies to access advanced memory.
Large cloud providers may secure capacity years in advance, leaving fewer products available for smaller AI companies.
Higher Memory Prices Could Increase AI Costs
If memory prices remain elevated, the cost of training and operating AI models may increase.
Cloud providers could pass some of those costs to enterprise customers.
This could make advanced AI services more expensive for smaller businesses.
Hardware Efficiency Will Become More Valuable
A prolonged shortage may encourage companies to develop more efficient AI models.
Techniques such as model compression, quantisation, memory optimisation, and efficient inference could become increasingly important.
The industry may shift from simply using more hardware to using available hardware more effectively.
Example Linux Commands for Monitoring Memory and AI Workloads
Administrators operating AI servers can monitor memory usage with:
free -h
This command displays total, used, available, and cached system memory.
To monitor memory activity continuously:
watch -n 1 free -h
To identify processes consuming the most memory:
ps aux --sort=-%mem | head -20
To monitor system performance in real time:
htop
For Nvidia GPU monitoring:
nvidia-smi
To refresh GPU statistics continuously:
watch -n 1 nvidia-smi
These commands cannot solve a global chip shortage, but they can help organisations improve infrastructure efficiency and identify workloads that consume excessive memory or GPU resources.
What Undercode Say:
The Shortage Is Becoming a Strategic Signal
Samsung’s forecast should not be viewed only as a prediction about chip availability.
It is also a signal that AI infrastructure demand is becoming more permanent.
The industry is moving beyond experimental AI deployments.
Companies are now planning multi-year infrastructure programmes.
Long-Term Contracts Could Reshape Market Power
The largest data-centre companies can negotiate large supply agreements.
Smaller companies may have less access to guaranteed memory capacity.
This could increase the competitive advantage of hyperscale cloud providers.
AI Growth Is Creating New Hardware Dependencies
The AI industry depends on more than powerful processors.
Memory capacity is becoming equally important.
Advanced packaging is also becoming a major constraint.
Power generation is another growing challenge.
Cooling infrastructure may become a limiting factor.
The AI race is increasingly an industrial race.
Samsung Is Turning Demand Into Financial Security
Long-term contracts provide visibility.
Minimum pricing can reduce downside risk.
Upfront payments may support factory investment.
These agreements could protect Samsung from sudden market changes.
The company is attempting to make memory revenue more predictable.
The Market Is Still Questioning AI Economics
Investors are not only measuring demand.
They are examining capital expenditure.
They are watching free cash flow.
They are asking when AI infrastructure will generate sustainable returns.
Strong chip sales do not automatically guarantee profitable AI services.
Samsung’s Internal Balance Is Becoming More Complex
The semiconductor division benefits from higher prices.
The mobile division faces higher component costs.
This creates tension between different parts of the company.
Samsung may need to improve efficiency across its consumer businesses.
HBM Could Determine the Next Stage of Competition
HBM is becoming a strategic product.
The companies that secure major AI customers may gain long-term advantages.
Samsung’s HBM4 growth could strengthen its position.
Competition with SK Hynix will remain intense.
Advanced memory leadership may become as important as processor leadership.
The Shortage Could Encourage Better AI Engineering
Limited hardware can drive innovation.
Developers may build smaller models.
Companies may optimise inference workloads.
Memory-efficient architectures could become more valuable.
Efficiency may become a competitive advantage.
The Semiconductor Cycle Is Evolving
Traditional memory cycles were driven by consumer electronics.
The AI era is being driven by data-centre investment.
Long-term contracts may reduce volatility.
However, they could also increase market concentration.
The next semiconductor cycle may be more structured than previous ones.
The Biggest Risk Is Overinvestment
Technology companies may build capacity faster than revenue grows.
If AI demand slows unexpectedly, expensive infrastructure could become underutilised.
This remains the largest financial risk.
Samsung’s contracts reduce some uncertainty.
They do not eliminate the possibility of an AI investment correction.
The Long-Term Opportunity Remains Powerful
AI demand continues to expand.
Memory requirements are increasing.
Data centres are becoming larger.
Samsung is positioning itself for a multi-year growth cycle.
The company’s strategy suggests confidence that AI infrastructure will remain a central technology priority.
✅ Samsung Reported an Extraordinary Increase in Semiconductor Profit
Samsung’s semiconductor operating profit rose more than 250-fold compared with the previous year, according to the reported financial figures.
The result demonstrates the scale of the memory-market recovery and the impact of AI-related demand.
The figures also show how rapidly semiconductor profitability can change during a strong pricing cycle.
✅ Samsung Is Expanding Long-Term Memory Supply Agreements
Samsung stated that it had signed agreements with the five largest global data-centre operators and was approaching additional deals.
The company did not publicly identify the customers, so the names of the participating organisations remain unconfirmed.
The reported contracts are expected to provide greater supply certainty and reduce investment risk.
✅ HBM Demand Is Supporting Samsung’s AI Strategy
Samsung expects HBM4 revenue to more than triple during the third quarter.
HBM is a critical component for advanced AI processors and high-performance computing systems.
Strong HBM growth could improve Samsung’s competitive position against SK Hynix and other memory manufacturers.
⚠️ The Exact Severity of the Shortage Through 2028 Remains a Forecast
Samsung expects supply constraints to continue into 2028, but future market conditions may change.
New factories, improved production yields, changing AI demand, or economic slowdowns could affect the forecast.
The prediction is based on current demand expectations rather than a guaranteed outcome.
Prediction
(-1) AI Infrastructure Costs Could Continue Rising Before the Market Stabilises
If memory shortages become more severe, the cost of building AI data centres may continue increasing.
Large technology companies may absorb some of these expenses, but smaller AI businesses could face higher barriers to expansion.
Higher hardware costs may also increase the price of cloud computing and advanced AI services.
(+1) Samsung Could Strengthen Its Position as a Long-Term AI Infrastructure Supplier
Samsung’s multi-year contracts may provide more predictable revenue and support major manufacturing investments.
Strong HBM growth could help the company gain market share in one of the most valuable segments of the semiconductor industry.
If AI demand remains strong, Samsung could emerge as one of the largest long-term beneficiaries of the global AI infrastructure expansion.
(+1) More Efficient AI Models May Become a Major Industry Priority
A prolonged hardware shortage could accelerate investment in smaller and more efficient AI systems.
Companies may focus more heavily on reducing memory requirements and improving inference efficiency.
The next major AI breakthrough may come not only from larger models, but from models that achieve more with less computing infrastructure.
Final Outlook: The AI Chip Race Is Becoming a Long-Term Industrial Transformation
Samsung’s latest results reveal a semiconductor industry entering a new phase. The company is no longer preparing only for the next quarter or the next product cycle. It is building supply relationships that may shape the AI infrastructure market for much of the decade.
The possibility of chip shortages lasting until 2028 highlights the enormous scale of global demand. At the same time, investor concerns show that AI growth still faces important financial questions.
Samsung’s record chip profits, expanding HBM business, long-term supply agreements, and U.S. manufacturing plans position the company strongly for the next stage of the AI era.
However, the future will depend on whether AI infrastructure investment produces sustainable economic returns. If demand remains strong, Samsung’s contracts may become a major strategic advantage. If spending slows, the industry could face another cycle of overcapacity and declining prices.
For now, one message is becoming increasingly clear: artificial intelligence is not only transforming software. It is reshaping the global supply chain for memory, manufacturing, energy, and computing infrastructure—and Samsung is preparing for that transformation to last far beyond the current boom.
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