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

The article is bullish on AI-driven earnings growth as a tailwind for the Nasdaq Composite, with the index up 102% over three years and potentially reaching 30,000 next year, about 22% above current levels. It highlights Nvidia and TSMC as dominant AI semiconductor leaders with strong pricing power, projecting Nvidia EPS growth of 75% this year and another 35% next year, and TSMC earnings that could reach $19.17 per share in 2027. The piece argues both stocks could deliver substantial upside, estimating Nvidia could rise 67% to $337 and TSMC about 57% to $575 under stated valuation assumptions.

Analysis

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.

Key Decisions for Investors

• Long NVDA vs. short a basket of weaker AI semiconductor exposure for 3-6 months; thesis is that the highest-quality earnings revisions keep compounding while capacity-constrained competitors get squeezed on margin. Target 2:1 downside-to-upside if the pair re-rates on the next earnings cycle.
• Long TSM on any 3-5% pullback over the next 2-4 weeks; this is a pricing-power, not growth, trade. Risk/reward is attractive because downside is cushioned by visible backlog, while upside comes from continued estimate revisions into the next 12 months.
• Add exposure to NVDA/TSM through call spreads instead of outright stock for the next earnings window; this captures revision momentum while defining downside if the market starts discounting AI capex saturation.
• Overweight AI infrastructure suppliers with oligopolistic positioning in advanced packaging, HBM, and test equipment versus generic hardware names; these are the second-order winners if the buildout persists over the next 12-18 months.
• Avoid chasing lower-quality AI beneficiaries that do not control supply or software distribution; use rallies to fade names where the market is paying for TAM rather than earnings durability.