Use cases for generative artificial intelligence (AI) seemingly emerge on a daily basis, providing fuel for upside for AI-related equities. Of course, that’s positive for investors. However, some market observers argue that enthusiasm should be tempered a bit. Artificial intelligence hasn’t achieved scale in many arenas as of yet.
The good news is that many of those same experts believe such scale will be achieved, confirming the long-term opportunity set with AI-related stocks and exchange traded funds such as the Invesco QQQ Trust (QQQ ) and the Invesco NASDAQ 100 ETF (QQQM ).
QQQ and QQQM, both of which track the Nasdaq-100 Index (NDX), are up 17% year-to-date as of June 14 and a significant reason why the ETFs are surging is exposure to AI names, including Nvidia (NVDA), Amazon.com Inc. (AMZN) and Microsoft (MSFT), among others. Regarding the artificial intelligence credentials of QQQ and QQQM, those are confirmed. However, the funds remain advantageous because they alleviate the stock-picking burden and are suitable for long-term investors. That’s pertinent because consensus wisdom Indicates AI scaling is in its early innings and could accelerate in the years ahead.
AI Long-Term Scaling Prospects Are Bright
Integral to the broader AI investment thesis and investors considering QQQ and QQQM are a few points. The artificial intelligence spending boom is young, but adopters need to be able to justify related expenditures.
“We are witnessing the start of a major investment boom and technological advance that may fundamentally affect all economic sectors,” according to UBS.
One of the factors that could trigger a massive wave of AI investment and justify related expenditures is increased productivity. Such efficiencies can act as margin and profit boosters, thus compelling more firms to invest in products and services purveyed by QQQ/QQQM member firms.
“While it is too early to accurately quantify the aggregate productivity enhancements from AI, anecdotal evidence suggests substantial efficiency gains," noted UBS. “For example, developers code up to 55% faster with the use of GitHub Copilot8. Boston Consulting Group estimates that customer service operations will become 30–50% more efficient when generative AI is implemented at scale.”
UBS highlighted enabling, intelligence, and applications as the three layers of AI spending. They noted potential beneficiaries of those trends include Alphabet (GOOG), Amazon, Meta Platforms (META), Microsoft, and Nvidia, among others. That quintet combines for approximately a third of the QQQ and QQQM rosters. That’s a potentially advantageous trait.The wave of AI spending, which is already forming, could ultimately be measured in the trillions of dollars.
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