5 AI Stocks to Buy Before the Next Leg of the Rally

The article highlights continued AI momentum with strong stock performances: Sandisk (up 600% in 2026) and the broader Nasdaq AI index up 60% over the past year. Nvidia is portrayed as the dominant compute platform, estimating $35B revenue per $50B of industry AI infrastructure spend, while Nebius’ partnership with Nvidia includes $2B investment and plans for 5+ GW of capacity by end-2030. Palantir (PLTR) cites commercial revenue up 133% YoY to $595M in Q1 and a full-year guidance increase to $7.65B–$7.662B, and Alphabet (GOOG/GOOGL) shows Google Cloud Q1 revenue of $20.02B (+63% YoY) with operating income tripling to $6.6B (+32.9% margin).

Analysis

The cleanest read-through is that AI is shifting from a pure GPU scarcity trade into a broader monetization stack: the best risk/reward is now in platforms that can both sell AI and use it to lower their own cost base. That favors GOOG/GOOGL and, to a lesser extent, MSFT and META over single-threaded infrastructure names, because they can absorb capex with ad load, cloud attach, and pricing power rather than needing perpetual top-line multiple expansion.

NVDA remains the toll collector, but that also makes it the most exposed to any pause in hyperscaler spend, power constraints, or a slower-than-expected deployment cadence over the next 1-2 quarters. NBIS is even more fragile: it needs customer precommitments and flawless execution to convert headline capacity announcements into durable gross margin, so any delay in ramp or financing hiccup would hit the equity harder than the article implies. SNDK is the second-order beneficiary most investors underweight; AI’s real bottleneck is increasingly memory, storage, and data movement, not just compute.

Contrarian take: the market may be overpaying for visible AI beta in NVDA/PLTR while underpricing the internal economics of Alphabet. GOOG has the rare combination of AI demand creation, cost deflation via TPUs, and cloud operating leverage, which can support both earnings and multiple durability over 6-18 months. The thesis is falsified if next hyperscaler capex prints show AI budgets normalizing or if GOOG cloud backlog fails to convert into margin expansion over the next two quarters.

Key Decisions for Investors

• Long GOOG/GOOGL vs short NVDA as a 3-6 month relative-value trade: prefer the platform that monetizes AI while reducing unit cost over the pure infrastructure toll collector; cover if NVDA revenue guidance re-accelerates or hyperscaler capex is revised up again.
• Add SNDK on pullbacks, not strength, as a 6-12 month bottleneck trade: storage and memory should capture the next wave of inference/agentic workloads; invalidate if data-center demand growth decelerates or pricing normalizes faster than expected.
• Avoid chasing NBIS after the partnership headlines; treat it as a watchlist name until utilization, gross margin, and financing terms prove the capacity build is earning back capital over the next 2-3 earnings cycles.
• Use PLTR as a momentum-sensitive trade, not a core compounder here: consider trimming into strength or structuring a call spread only if commercial growth stays above 100% and guidance keeps rising; otherwise multiple compression can outweigh revenue beats.
• Monitor MSFT and META capex commentary over the next earnings round as the key falsifier for the entire AI infrastructure complex; a capex slowdown would hit NVDA first and ripple to NBIS and SNDK with a 1-2 quarter lag.