Global semiconductor shortages are expected to continue until at least 2028 [2].

This prolonged deficit threatens to slow the deployment of artificial intelligence infrastructure and increase costs for hardware manufacturers across multiple sectors.

Chris Maxey, founder of Wealthspire, said the shortage is being driven by an unprecedented surge in demand for data-center chips. This demand is fueled by the rapid expansion of AI capabilities, which requires specialized processing power that current manufacturing capacities cannot meet [1].

Financial commitments from the largest technology companies underscore the scale of the problem. Hyperscalers have pledged more than $6 trillion in AI spending through 2030 [1]. This massive investment creates a sustained pressure on the supply chain that is unlikely to ease in the short term.

Samsung has provided a similar outlook regarding specific components. The company said the memory chip shortage is expected to worsen through 2027 and last until 2028 [3]. Memory chips are essential for the high-speed data processing required by large language models, and generative AI tools.

While some sectors of the semiconductor market have stabilized since previous crises, the AI-specific hardware market remains volatile. The gap between the ability to design advanced chips and the physical capacity to fabricate them remains a primary bottleneck [1].

Industry analysts said that the timeline for recovery depends on the construction of new fabrication plants and the scaling of advanced packaging techniques. However, the sheer volume of planned spending by tech giants suggests that supply will struggle to catch up with demand for several years [1].

“Global semiconductor shortages are expected to continue until at least 2028.”

The extended timeline for chip availability indicates that the AI boom is not merely a software trend but a physical infrastructure challenge. Because hyperscalers are committing trillions of dollars to hardware, the semiconductor industry is facing a structural imbalance where demand is decoupled from traditional economic cycles, potentially leading to higher long-term costs for cloud computing and AI services.