Three Wall Street analyst picks are drawing fresh attention as AI-driven demand reshapes the software, memory, and semiconductor equipment sectors: Datadog, Micron Technology, and Lam Research. Top-ranked analysts at Bank of America, UBS, and Mizuho have each raised price targets on the trio in recent weeks, pointing to structural tailwinds they believe the broader market has not fully priced in.
| Company | Ticker | Analyst | New Price Target | Rating |
|---|---|---|---|---|
| Datadog | DDOG | Koji Ikeda, BofA | $260 | Buy |
| Micron Technology | MU | Timothy Arcuri, UBS | $1,625 | Buy |
| Lam Research | LRCX | Vijay Rakesh, Mizuho | $380 | Buy |
Datadog: AI-Native Customers Now Drive 8.5% of ARR
Bank of America’s Koji Ikeda lifted his Datadog price target to $260 from $225 after an investor webinar with Cognizant’s senior director of North American business, citing improving demand for best-of-breed infrastructure software. He flagged Datadog and JFrog as companies positioned to beat both BofA and Street estimates.
The numbers behind the call are worth parsing. Datadog’s Q1 2025 results showed revenue of $762 million, up 25% year-over-year, with 3,770 customers generating at least $100,000 in annual recurring revenue, compared to roughly 3,340 a year earlier. The AI-native customer cohort now accounts for 8.5% of total ARR, up from 3.5% twelve months ago. That kind of mix shift is what Ikeda is betting accelerates.
There is a cost side to watch. The official Q1 press release shows a GAAP operating loss of $(12) million and a non-GAAP gross margin of 80.3%, down from 83.3% a year ago. Margin compression at this scale is not alarming, but it narrows the cushion if revenue growth slows. Ikeda’s second-quarter revenue growth outlook of more than 30% would need to hold to justify the new target.
Micron: Long-Term Agreements Anchor the $1,625 Target
UBS analyst Timothy Arcuri’s move to a $1,625 target from $535 is the boldest call of the three. His thesis rests on structural changes in how memory is sold, not just cyclical demand. New long-term agreements across the industry carry fixed-volume commitments and partial price floors, contrasting with the volume-only offtake deals of prior cycles.
Arcuri’s supply chain checks suggest up to 30% of DDR memory volumes could soon be locked in at pricing only slightly below current spot levels. That stability, if it holds, underpins his revised EPS estimates: $155, $167, and $117 for 2027, 2028, and 2029, respectively, against prior estimates of $133, $122, and $77. He projects more than $400 billion in free cash flow over that span.
Recent results support the optimism. Micron’s fiscal Q1 2026 revenue reached $13.64 billion, up 57% year-over-year. Its Cloud Memory Business Unit nearly doubled to $5.28 billion, running at 66% gross margins on HBM, high-capacity DIMMs, and low-power server DRAM. Arcuri ranks second among more than 12,200 analysts on TipRanks, with an 81% profitable-rating rate and an average return of 56.6%.
Lam Research: WFE Spending Projections Keep Rising
Mizuho’s Vijay Rakesh raised his Lam Research target to $380 from $330, now modeling wafer fabrication equipment spending at $153 billion in 2026 and $190 billion in 2027. Increased capex from TSMC, Samsung, and Micron drives both numbers higher, with total memory WFE investment projected near $112 billion this year alone.
Lam’s own guidance points in the same direction. The company’s March 2026 quarter press release reported revenue of $5.84 billion, a non-GAAP operating margin of 35.0%, and Q4 guidance of $6.2 to $7.0 billion. The midpoint of $6.6 billion implies continued sequential growth. Separately, Lam’s own Q3 2026 earnings call pegged its WFE market estimate at $140 billion with an upward bias, below Rakesh’s $153 billion but trending in the same direction. The gap between the two figures may indicate room for further estimate revisions.
Rakesh also sees a $40 billion node-transition spending cycle in NAND, most of it landing before end of 2027. That near-term timing is the lever: if NAND node transitions accelerate on schedule, Lam stands to benefit disproportionately as the steady WFE outperformer versus peers.
What the Wall Street Analyst Picks Have in Common
All three of these Wall Street analyst picks sit at the infrastructure layer of the AI trade. They are not consumer apps or model builders. They supply the observability software, memory chips, and fabrication equipment that make AI workloads possible at scale. That positioning tends to be stickier than the model layer, where competitive pressure is intense and pricing power is harder to defend.
The shared risk is macro sensitivity. Memory pricing can reverse quickly, enterprise software spending can pause if IT budgets tighten, and WFE orders can slip if chipmakers defer capacity. For Micron in particular, the LTA thesis depends on counterparties honoring multi-year commitments through any downturn.
The next hard data point for all three arrives with the next round of earnings. Datadog’s ability to sustain 30%-plus revenue growth in Q2 is the first test of Ikeda’s conviction.
