September Effect: 3 AI Stocks to Buy on a Potential Market Pullback

The article identifies Palantir, Marvell, and Snowflake as AI beneficiaries to buy on a market pullback, while cautioning that all three trade at elevated valuations. Palantir reported 93% year-over-year revenue growth and 157% net-dollar retention; Snowflake grew revenue 35% with 126% retention and expects 37%-38% growth next quarter. Marvell is positioned for AI-data-center optical demand and custom-chip growth, with Piper Sandler estimating its Alphabet-related program could eventually generate $18 billion in annual revenue.

Analysis

The investable distinction is not “AI exposure” but where incremental enterprise AI spend lands: PLTR monetizes deployment and workflow ownership, SNOW monetizes data access/compute, while MRVL is a hyperscaler capex derivative. PLTR's retention-driven narrative supports operating leverage, but its premium multiple leaves it most vulnerable to even a modest deceleration in U.S. commercial bookings or billings. SNOW has a cleaner re-rating path if AI workloads lift consumption growth without requiring a large sales-and-marketing step-up; its key debate remains whether AI workloads are truly incremental versus cannibalizing conventional warehouse spend.

MRVL's upside depends on custom silicon programs converting from design wins into production volumes, a process with customer-concentration, qualification, and pricing risks that equity markets often underwrite too early. The cited long-run Alphabet revenue potential should be treated as an unverified scenario rather than forecastable backlog; hyperscalers retain substantial bargaining power and can dual-source networking/ASIC components. A broader AI-capex pause would hit MRVL earlier than PLTR or SNOW because hardware orders are exposed to inventory digestion and deployment timing.

Near term, a market-led risk-off pullback would likely create better entry points in SNOW than PLTR: both are long-duration equities, but SNOW has more room for a consumption-growth upside surprise to drive estimate revisions over 1-3 months. Over 6-18 months, the contrarian risk is that model commoditization shifts value away from application-layer vendors toward cloud platforms and proprietary data owners; AMZN, MSFT, and GOOG can bundle competing data, model, and agent capabilities at lower standalone cost. The thesis is falsified by weakening net retention/remaining-performance-obligation trends for PLTR and SNOW, or by delayed custom-chip revenue ramps and lower data-center capex guidance for MRVL.

Key Decisions for Investors

• Watch for a 15-20% broad software-led drawdown before initiating a long SNOW position; target a 20-30% upside over 6-12 months if product-revenue growth reaccelerates and net retention stabilizes or improves. Exit/reassess on two consecutive quarters of consumption deceleration or material guide-down.
• Maintain PLTR as a tactical, not core, AI-software exposure: buy only after a 20%+ correction or an earnings reset that preserves commercial-bookings momentum. Upside is multiple-supported rather than purely estimate-driven; risk is a 25-35% de-rating if growth normalizes faster than consensus.
• Avoid chasing MRVL on announced design-win narratives. Create an alert for disclosed production revenue, gross-margin progression, and hyperscaler capex guidance; initiate only once revenue conversion is independently visible. A long MRVL / short SOXX hedge can isolate custom-silicon execution if confirmation arrives.
• For a 6-12 month relative-value expression, favor long SNOW / short PLTR in equal dollar terms after a software rebound: SNOW offers greater estimate-revision optionality from AI consumption, while PLTR carries greater valuation sensitivity. Close if PLTR's commercial growth materially outpaces SNOW product-revenue growth for two quarters.