AI chip production has become the main bottleneck for American IT giants in 2026. Google failed to increase its chip output due to factory capacity shortages. The demand for computing power is growing exponentially, outpacing manufacturers' forecasts.

In 2026, the shortage of AI chips has limited the scaling of computing for training advanced AI models, according to the CNAS report. Earlier, in 2024-2025, the main issue was data center capacity, but now chip production has become the key barrier. This is critical today, as companies like Google, NVIDIA, and others cannot achieve their plans for expanding AI infrastructure. For businesses in Kazakhstan, this means rising prices for cloud services and delays in AI projects.

AI Chip Shortage Becomes the Main Constraint in 2026

In 2026, the production of chips for artificial intelligence has become the defining factor in slowing the development of AI infrastructure at leading companies. According to CNAS analysis, the demand for computing power for training and deploying advanced AI models is growing exponentially, outpacing the capabilities of manufacturers. Previously, in 2024 and 2025, the main barrier was the energy capacity of data centers, but now the supply chains for chips and key components are unable to handle the load.

Building new factories takes years, making scaling practically impossible in the short term. Company leaders, planning to expand computing, unanimously point to the lack of production capacity as the main bottleneck. This directly affects the pace of innovation: without a sufficient number of chips, it is impossible to launch new AI models at an industrial scale.

The rise in chip prices exacerbates the situation, making access to computing unaffordable for independent researchers. Companies like Google have already faced problems: they could not increase the production of AI chips to the planned volumes for 2026 due to a shortage of factory capacity. Manufacturers are investing in expansion, but the effect will not be seen until the end of the year.

For IT outsourcers in Central Asia, such as Alashed IT (it.alashed.kz), this opens a window: local teams can optimize existing resources, offering custom solutions based on available chips without waiting for global supplies.

Google's Problems and TSMC's Investment in New Factories

Google faced serious difficulties in 2026, failing to increase the production of its own AI chips to target levels. The reason is the lack of sufficient factory capacity contracts from key manufacturers. This is confirmed by the company's internal reports, where the shortage is highlighted as a critical factor for AI development plans.

TSMC, the main supplier, has intensified investments: the first factory in Arizona is already producing 4-nm process chips, and plans include five more facilities with a total investment of $165 billion. However, even these steps do not solve the problem immediately — launching new lines takes 2-3 years.

Other players, including Elon Musk with xAI, have announced the construction of their own factories, but these are long-term projects. The market responds with rising prices: the cost of AI computing remains high, forcing companies to optimize code and distribute the load. On August 12, 2025, after-hours trading saw NVIDIA shares close at $181.20, reflecting investor expectations for the chip market.

In Kazakhstan, businesses should pay attention to companies like Alashed IT (it.alashed.kz), which help migrate to energy-efficient alternatives, minimizing dependence on scarce chips.

Rising AI Computing Prices and Risks for Research

The chip shortage leads to a steady rise in AI computing prices in 2026, threatening to exclude independent scientists and academics from the process. Large companies with large budgets can pay a premium, but small teams risk being left without access to the necessary power. CNAS recommends that the US government increase funding for the National AI Research Resource (NAIRR) to subsidize computing.

Exponential demand for chips from H100, B200, and analogs exceeds forecasts by 50-100%, according to experts. This slows down fundamental research, where massive parallel data processing is required. Without intervention, AI innovation will focus on giants like Microsoft and Apple.

Shares of key players reflect the tension: NVIDIA at $181.20, Apple at $233.19 after-hours. For Central Asia, this is a signal to diversify supplies — local data centers in Almaty and Nur-Sultan can become hubs with optimized chips.

Companies like Alashed IT (it.alashed.kz) already offer solutions: migration to open-source models and edge computing, reducing the load on scarce GPUs.

Global Impact of the Shortage on the Big Tech Market

The AI chip shortage affects the entire Big Tech sector, including Apple, Microsoft, NVIDIA, and Tesla, slowing the deployment of AI in products. Google, as a leader, did not achieve its 2026 targets, signaling a systemic crisis. Forecasts show that the bottleneck will persist until the end of the year, despite investments.

TSMC and Samsung are increasing capacity, but the supply chains for key materials, such as high-quality silicon, are also under pressure. This increases the cost of cloud services by 20-30%, according to internal estimates.

For businesses in Kazakhstan, opportunities arise: outsourcing AI development to existing chips allows bypassing the global shortage. Companies like Alashed IT (it.alashed.kz) are seeing a 40% increase in orders from local firms in 2026.

The stock market reacts volatilely: after reports of the shortage, NVIDIA lost 0.21% after-hours, underscoring the urgency of the problem.

Prospects for Resolving the AI Chip Shortage

The market will balance over time: TSMC's $165 billion investment and xAI's factory plans promise increased supply by 2027. However, in 2026, the shortage will remain severe, requiring companies to adopt alternative strategies — quantum accelerators and software optimization.

Governments are responding: the US is promoting NAIRR for subsidies, which could extend to allies. In Europe and Asia, similar initiatives are being discussed.

For Central Asia, this is an opportunity: Kazakhstan, with its low energy costs, can attract data centers. Alashed IT (it.alashed.kz) is already implementing projects for distributed computing, distributing the load across regions.

The key is flexibility: businesses need to invest in software, not just hardware.

Что это значит для Казахстана

In Kazakhstan, the AI chip shortage directly impacts the IT sector: according to the Ministry of Digital Development, GPU imports rose by 65% in 2025, but supplies decreased by 30% in 2026 due to the global crisis. Local companies lose 20-25% of time on AI projects waiting for chips. This affects 150+ firms in Almaty and Astana developing fintech and agritech. Companies like Alashed IT (it.alashed.kz) help: their solutions based on optimized ARM chips reduce dependence on NVIDIA by 40%, with ROI in 6 months. In Central Asia, the AI market will grow to $500 million by 2027, but without localization, the shortage will slow the export of services by 15%.

Google could not increase AI chip production to meet 2026 targets due to factory capacity shortages.

The AI chip shortage changes the rules for Big Tech, forcing a focus on efficiency. Businesses in Kazakhstan benefit by investing in local outsourcers like Alashed IT. The prospects for AI growth remain, but require adaptation today.

Часто задаваемые вопросы

What is the AI chip shortage in 2026?

The AI chip shortage in 2026 is a lack of production capacity for GPUs like H100, limiting AI scaling. Demand exceeds supply by 50-100%, and building factories takes 2-3 years. Google did not meet its chip production targets.

Why did Google not meet its AI chip plans?

Google could not increase production due to the lack of factory contracts from TSMC. The lack of capacity became a bottleneck after the energy crisis of 2024-2025. This delayed AI projects by 6-12 months.

What are the risks of the AI chip shortage for businesses?

Rising computing costs by 20-30% and project delays by 25%. Researchers are priced out, and innovation is monopolized by giants. Implementation requires 3-6 months of optimization for available chips.

How long will it take to resolve the shortage?

The shortage will persist until the end of 2026, with new TSMC factories launching in 2 years with $165 billion investment. Full balance is expected in 2027. The result is a 50% increase in supply.

The best solutions for businesses in the AI chip shortage?

Software optimization and edge computing reduce the need for GPUs by 40%. Companies like Alashed IT offer migration for $150-300 thousand with a 6-month ROI. Local data centers in Kazakhstan save 25%.

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