There’s a daily onslaught of AI headlines and often tantalizing intraday moves notched by some related stocks. Some investors are tempted to take short-term views of the artificial intelligence investment thesis.
Altering that thinking could be advisable. That’s because story stocks, such as Nvidia (NVDA), don’t reach that status overnight. Rather, those stories — the big gains — are penned over longer holding periods. That indicates patience is a virtue when it comes to ETFs like the Invesco QQQ Trust (QQQ) and the Invesco NASDAQ 100 ETF (QQQM).
Indeed, those ETFs have impressed in recent months while delivering solid year-to-date gains. But market participants should consider taking the long view. That’s particularly so regarding the AI leverage offered by the Invesco funds. For example, Morgan Stanley estimates AI could lead to $40 trillion in corporate operational efficiencies, ushering in a tidal wave of AI-related spending. That’s a theme that could take years to develop in earnest.
QQQ Investors Don’t Need to Wait Long
Time can be a matter of perspective. But when it comes to AI spending materializing, investors allocating to ETFs like QQQ and QQQM may not need to wait for benefits to materialize.
“I was honestly shocked when we actually put all the pieces together to figure out the total CapEx on AI infrastructure, the number is a bit over $3 trillion over the next few years through 2028,” noted Stephen Byrd of Morgan Stanley.
AI infrastructure spending is a prime example of the oft-discussed AI “arms race.” This race has substantial implications for assets such as QQQ and QQQM. Alone, the AI competition between the U.S. and China, which was on full display earlier this year amid the DeepSeek headlines, could be a positive in terms of longer-ranging AI expenditures.
The AI arms race could also be a catalyst for mergers and acquisitions. QQQ and QQQM are large/mega-cap ETFs. That implies member firms are more likely to be buyers than sellers. For investors, that’s all right, because many of the ETFs’ biggest, most AI-correlated names have strong balance sheets. They’re also among the most cash-rich companies in the U.S.
“There is a little bit of an arms race particularly amongst the hyperscalers and the bigger companies and to just keeping up with innovation,” observed Enrique Perez-Hernandez of Morgan Stanley. “So M&A is becoming more… Relevant.”
The impetus for more artificial intelligence consolidation has already arrived. That’s because it’s clear top-level decision-makers at large companies are prioritizing better deployment of this disruptive technology, indicating patience can reward with ETFs like QQQ and QQQM.
“I can’t think of any client who currently is not thinking at the C-Suite level at the board level in great detail about how AI becomes part of their strategy,” concluded Byrd.
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