Buy 2 Artificial Intelligence (AI) Stocks That Are Crushing Nvidia and Palantir in 2026

Micron shares are up 59% YTD and Comfort Systems is up 77%, both benefiting from AI data center demand. Micron reported fiscal Q2 revenue of $23.8B, up 196%, with non-GAAP EPS of $12.20 and analysts expecting 75% annual earnings growth through fiscal 2028; the median target of $550 implies 21% upside. Comfort Systems posted 41% revenue growth to $2.6B, backlog doubled to $12B, and its median target of $1,710 implies 4% upside.

Analysis

The market is starting to price AI less as an “application story” and more as a physical throughput problem. That shifts economic rent toward the bottlenecks: memory, power, cooling, and systems integration, which explains why the second derivative is stronger in MU and FIX than in the headline AI platforms. The interesting second-order effect is that the more hyperscalers try to accelerate deployment, the more they reinforce a near-term scarcity regime for upstream inputs, even if end-demand for AI software stays uneven.

MU is the cleaner momentum expression because memory pricing has leverage to both volume and price, but the trade is also the most cyclical. The key risk is not demand weakening first; it is capacity rationalization lagging demand by 12-24 months, which typically turns a supernormal margin regime into a rapid earnings air pocket. In other words, the consensus may be underestimating how fast the stock can rerate upward over the next two quarters while overestimating how durable the current EPS base will be beyond the cycle peak.

FIX is benefiting from a different, more structural bottleneck: data centers need physical commissioning, cooling, and uptime engineering, and that backlog creates a visibility window that can last several quarters. But this is a lower-beta compounder than a true dislocation trade; the market is already treating it as a quality infrastructure beneficiary rather than a mispriced growth asset. The bigger setup is relative-value: if AI capex remains resilient, FIX should keep outperforming the broad industrial complex, but its upside is likely more in earnings compounding than multiple expansion.

The contrarian miss is that investors may be too focused on NVDA/PLTR as the AI proxies and not enough on who gets paid when the buildout shifts from chips to installation. If memory stays tight and data center buildouts remain aggressive, the winners will broaden before they narrow, which argues for owning the picks-and-shovels with the most direct pricing power while fading the most crowded high-multiple software names on any strength.

Key Decisions for Investors

• Long MU on a 3-6 month horizon; use pullbacks to initiate/add. Target is continued multiple support as earnings revisions stay upward, but trim strength if channel checks suggest memory lead times are inflecting higher capacity additions.
• Pair trade: long MU / short PLTR for 3-6 months. This isolates tangible AI capex monetization versus crowded valuation risk; the pair favors the name with pricing power and clearer earnings revision momentum.
• Hold or add FIX on dips for a 6-12 month trade, but size smaller than MU. Upside is more durable but less explosive; use it as a quality AI-infrastructure compounder, not a home run.
• Hedge AI beta by shorting a basket of high-multiple software on strength against long infrastructure beneficiaries. The risk/reward improves if the market starts rotating from narrative to cash-flow realization.
• Set a tactical alert on MU for signs of memory capacity announcements or ASP rollovers; that is the catalyst that can flip the trade from momentum to mean reversion within 2-4 quarters.