
What happened
Major AI-related ETFs have fallen sharply in recent weeks—the Dan Ives Wedbush AI Revolution ETF dropped 10% since June 1, and the iShares Semiconductor ETF fell 15% from its June 22 peak (as of July 13). Nvidia and other AI infrastructure leaders have driven earlier gains, but geopolitical turmoil and investor questions about whether massive AI spending will deliver returns have weighed on the sector.
Why it matters
The article argues the full AI adoption story is still in its earliest phases, with companies and individuals only beginning to regularly use AI and apply it to real-world needs. If true, infrastructure winners like Nvidia (trading at 22x forward earnings) and Microsoft (at 20x estimates) may continue generating growth as their products remain essential—and new AI-powered winners could emerge as companies gain efficiency and lower costs. The current dip may be a buying signal rather than a sign of trouble ahead.
What to watch
Tech companies are planned to invest nearly $700 billion(約110兆円) this year alone in AI infrastructure build-out, responding to exploding demand for AI workload capacity. Industries such as robotics and pharmaceuticals may come to rely heavily on AI in coming years; how quickly those use cases materialize will shape whether the recovery is real.
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AI stocks have been the main driver of gains in the S&P 500 in recent years, with companies like Nvidia and Amazon generating significant revenue growth from the early stages of the AI boom. The Dan Ives Wedbush AI Revolution ETF jumped nearly 50% from its launch a year ago, and the iShares Semiconductor ETF soared more than 200% over the past three years. However, recent weeks have brought a sharp reversal as investors grow cautious, weighed down by geopolitical turmoil, inflation concerns, and skepticism about whether tech companies' enormous AI spending will deliver commensurate returns.
The article frames this moment as potentially pivotal: the boom so far has centered on infrastructure development—building and training AI models—but the real growth catalyst may come from widespread adoption and real-world use. If industries such as robotics and pharmaceuticals begin to rely heavily on AI for major advancements, and if companies use AI to gain efficiency and lower costs, then the long-term opportunity remains intact. The decline, on this reading, is a midcycle pullback in an early-stage boom, not a sign the thesis has broken. Infrastructure leaders are still trading at what the article characterizes as reasonable multiples: Nvidia at 22x forward earnings and Microsoft at 20x—levels that may reflect pessimistic expectations and leave room for revaluation if the adoption curve accelerates.
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