Nvidia (NVDA) is just one example, but the company and its high-flying stock prove an important, simple point: semiconductors are the foundation on which the AI revolution resides. There are, of course, plenty of related investment implications.
AI demand and expectations of future growth are some reasons the widely followed PHLX Semiconductor Index is up 27.12%. Fortunately for investors engaged with the Invesco QQQ Trust (QQQ) and the Invesco NASDAQ 100 ETF (QQQM), those funds are homes to many of the stocks also residing in the PHLX gauge.
QQQ and QQQM allocate over half their rosters to technology equities. And chip names figure prominently in those equations. Close to 20 semiconductor stocks dot the lineups of both Invesco ETFs. That confirms the funds are levered to that industry’s trends. Those include the possibility of a chip shortage caused by swelling AI demand.
Chip Shortage a Real Possibility
Shortages aren’t new in the semiconductor arena. Such events have occurred for various reasons, including labor strife, political turmoil and even bad weather. The last such instance of chip supply crimping happened in 2020. That’s when global supply chains collapsed due to the coronavirus pandemic. This time, it could easily be AI that triggers another semiconductor shortage supply crunch.
“The AI-driven surge in demand for graphics processing units alone could increase total demand for certain upstream components by 30% or more by 2026,” according to a new report by Bain & Co.
That forecast of 30% increase or more for some types of chips is highly relevant to investors and the semiconductor producers dwelling in QQQ and QQQM. That’s because, as Bain noted, 20% increases can trigger shortages in the notoriously sensitive semiconductor supply chain. And 20% could easily be exceeded as new AI adopters emerge and earlier adopters allocate more capital to AI.
Long-Term Opportunity for Some QQQ/QQQM Chip Holdings
“Accelerating adoption of AI across industries will pressure the supply of graphics processing units (GPUs) for data centers, which is due to a seemingly insatiable demand for computing resources to train and operate large language models (LLMs) collides with supply chain constraints. In addition, the coming proliferation of AI-enabled devices appears poised to jumpstart a wave of purchases of new personal computers (PCs) and smartphones, which has major implications for the broader semiconductor supply chain,” added Bain.
Regarding chip end markets relevant to QQQ and QQQM, familiar industries such as PCs and smartphones must be discussed. That’s because those devices are increasingly leaning into AI. And that potentially brings long-term opportunity for some QQQ/QQQM chip holdings.
“Personal device makers are already rapidly embedding AI capabilities directly into their products. To accommodate neural processing engines for on-device AI, the average notebook core processing unit (CPU) and smartphone processor have respectively added about 5% and 16% more silicon surface area,” concluded Bain.
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