Prediction: The Nasdaq Could Soar to 30,000 by 2027. These Are the Best Artificial Intelligence (AI) Growth Stocks to Own Until Then.

The real trade is not “AI is good for tech” but “capacity scarcity is migrating up the stack.” When leading-edge packaging, wafer starts, and advanced nodes stay tight, pricing power compounds for the two companies that sit at the chokepoints: the designer with demand visibility and the foundry with constrained supply. That combination is unusually durable over 12-24 months because incremental AI capex is still being funded by hyperscaler balance sheets, not by cyclical end-demand, so order pullbacks are less likely to normalize the ecosystem quickly.

Second-order beneficiaries are the adjacent supply-chain names that reduce single-source risk for either NVDA or TSM: advanced substrate, test/inspection, HBM, and power-delivery vendors should see mix improvement even if top-line growth moderates. The more interesting loser is any AI chip challenger that lacks both software lock-in and manufacturing priority; even if it matches performance on paper, it is forced to compete on price while waiting behind the same constrained capacity queue. That usually compresses gross margins before market share shows up in reported revenue.

The main risk is not earnings disappointment but multiple compression if investors decide the AI infrastructure buildout is “already priced” and rates stay sticky. In that scenario, the setup is vulnerable to a 1-2 quarter pause in hyperscaler capex or a regulatory/export shock that disrupts shipment timing rather than demand itself. The market can absorb slower unit growth if pricing holds; it struggles if both price and volume assumptions get questioned simultaneously.

Consensus is probably underestimating how much of the upside is already embedded in the obvious winners and missing the duration of the bottleneck. A 30x multiple for these names is not cheap, so the next leg likely comes from estimate revisions, not rerating. That favors owning the strongest operating leverage to AI infrastructure while fading the lower-quality AI basket that relies on narrative rather than supply-constrained earnings power.