Stifel reiterates Snowflake stock Buy rating on AI growth potential

Snowflake reported $1.23B in product revenue (+30% YoY) and remaining performance obligations of $9.77B (+42%), aided by a $400M deal; trailing twelve-month revenue growth was 29% and gross margin 67%. Management emphasized AI-driven expansion (Cortex Code, Intelligence, Project SnowWork in limited preview) as drivers of future consumption and said it can offset potential AI-related margin pressure via COGS and opex efficiencies; InvestingPro tips forecast EPS of $1.95 for fiscal 2027. Analyst reactions are broadly constructive but mixed on valuation: Stifel reiterated Buy with a $205 PT, BofA $275 Buy, TD Cowen $255 Buy, Barclays Equalweight $192, while Macquarie cut its PT to $177 (Neutral).

Analysis

Snowflake's shift from pure storage/warehouse to an autonomous AI platform creates a classic platform-versus-point-product inflection: if successful, it converts high-ARPA customers into platform customers with sticky, multi-workload consumption (analytics + model inference + embedding stores). That stickiness also raises bargaining leverage with hyperscalers for managed compute economics; the negotiation outcome (commitment discounts vs pass-through compute) will drive whether incremental AI revenue drops to hyperscalers or accrues to Snowflake.

A meaningful near-term catalyst set will be customer-level unit economics: within 2-4 quarters we should see whether AI workloads on Snowflake are accretive on a per-workload gross margin basis or merely volume growth subsidized by the company. If Snowflake proves positive gross margin per AI workload, upside re-rating is likely; if instead it leans on subsidies to drive adoption, expect notable margin compression within 6-12 months and downward guidance volatility.

Second-order supply effects matter: rising enterprise AI demand will push more GPU spend into public clouds, increasing spot/pricing pressure for hyperscalers and creating a capacity premium that Snowflake can exploit or be forced to absorb. That dynamic also opens a window for ISV ecosystems on Snowflake — independent vendors can rapidly expand TAM, but they also lower switching costs for customers if hyperscalers bundle competing managed stacks.

On valuation and timeline, the asymmetric payoff is clear: the market appears to underweight platform optionality (ecosystem + ISV monetization) while pricing in the risk of near-term margin stress. The trade is therefore binary on execution: public customer references demonstrating profitable AI consumption economics (3–5 anchors) and demonstrable margin expansion on AI workloads within 12 months should re-rate the stock materially; failure to show that will compress multiples over the next 6–12 months.

Key Decisions for Investors

• Buy SNOW (equity) — Allocate 2–3% of risk budget, stagger purchases over 6–12 weeks on any pullbacks; target +60% in 12–18 months, hard stop -25% from entry. Rationale: capture platform optionality while limiting downside from near-term margin volatility.
• Buy NVDA (options) — Buy 9–12 month call exposure equal to 1% portfolio notional to play GPU/TAM tailwind; target 3:1 upside if enterprise AI spends accelerate, stop if implied volatility doubles without fundamental adoption signals. Rationale: GPU scarcity/pricing is the primary supply-side lever for Snowflake’s AI economics.
• Pair trade: Long SNOW / Short SPLK (or comparable legacy analytics) — Size as a market-neutral 1–1 pair for 12 months, target relative outperformance of 25–35%; exit if pair underperforms by 15% in 3 months. Rationale: capture migration from legacy on-prem analytics to platform-first architectures.
• Options asymmetric: Buy an 18–24 month SNOW call spread (long lower strike, short ~2x higher strike) sized to 1–1.5% portfolio and finance with selling near-term cash-secured puts (same notional) — net delta positive, limited downside if you’re assigned. Rationale: preserves upside optionality to platform re-rating while monetizing near-term time decay to fund exposure.