2 Artificial Intelligence Stocks You Can Buy and Hold for the Next Decade

Nvidia reported $1.87 in EPS in the latest quarter, up 140%, and still controls 86% of AI data center revenue, while Taiwan Semiconductor generated nearly $36 billion in Q1 2026 revenue, up 41%, with EPS of $3.49 per ADR. The article argues both companies remain long-term AI leaders and are trading at relatively attractive P/E ratios versus the tech sector, with Nvidia at 32x and TSMC at about 38x. Overall, this is bullish stock-picking commentary rather than new material company news.

Analysis

The key market implication is not simply that NVDA and TSM remain winners, but that AI capex is still broadening faster than the market has priced. If compute monetization is truly improving, the next leg of upside likely comes from the infrastructure layer and the ecosystem vendors with operating leverage to incremental GPU deployments, while lower-quality AI names without real cash generation should see relative multiple compression.

NVDA’s risk/reward is increasingly about duration rather than demand. The near-term upside is protected by scarcity and pricing power, but the hidden fragility is that a single quarter of capex digestion or hyperscaler pull-forward unwinds the “parabolic” narrative quickly; that would hit semiconductor beta broadly before it shows up in fundamentals. AMD remains the obvious share-take story, but the second-order effect is that even if it gains modest sockets, it can still underperform if investors focus on gross margin quality, software lock-in, and ecosystem moat versus raw unit growth.

TSM is the cleaner way to own structural AI without paying for peak enthusiasm, but it is also the best proxy for global semiconductor concentration risk. The market is underestimating how much geopolitical risk premium should be embedded in a name that sits at the center of advanced-node supply; any Taiwan headline would cause a sharp, temporary de-rating even if end-demand is intact. Over a multi-year horizon, the real catalyst is packaging, node migration, and advanced manufacturing scarcity, which should preserve pricing power longer than consensus expects.

The contrarian miss is that this is less a ‘buy the winners’ story than a ‘buy the bottleneck’ story. If AI demand keeps compounding, the companies controlling manufacturing capacity and accelerator economics should capture the lion’s share of incremental profit pools, while application-layer beneficiaries may face faster commoditization. That makes the current setup attractive for quality longs, but not for chasing every AI-linked name indiscriminately.

Key Decisions for Investors

• Go long NVDA on any 3-5% pullback over the next 1-2 weeks; use a 6-9 month horizon. Risk/reward favors owning the leader, but size modestly because the multiple can de-rate 15-20% on any capex pause even if fundamentals stay strong.
• Initiate a core long TSM position for 12+ months; add on geopolitical-driven drawdowns rather than strength. The upside comes from structural scarcity and packaging leverage, while the main risk is a headline gap-down that can be hedged rather than avoided.
• Pair trade: long NVDA / short AMD for a 3-6 month horizon. The thesis is that share gains alone will not offset ecosystem and margin disadvantages; this works best if the market shifts from ‘AI growth at any price’ to ‘cash conversion and durability.’
• Avoid chasing lower-quality AI infrastructure names with no earnings visibility; instead, rotate capital toward cash-generative semis. The setup is better for names with operating leverage and balance-sheet strength than for story stocks that need continuous re-rating.
• For TSM, consider buying downside protection via 3-6 month put spreads if position size is meaningful. This preserves upside from AI capex expansion while limiting tail risk from Taiwan-specific geopolitical shocks.