Q: What is driving Snowflake’s recent revenue acceleration? A: Snowflake AI-driven revenue growth is driven largely by its AI products and faster migrations of existing workloads onto the core data platform, with management saying the AI product group accounted for roughly half of the recent acceleration. Product revenue grew 37% year over year in fiscal Q2 2027 to $1.49 billion, and management raised fiscal 2027 product revenue guidance to $6.07 billion, representing about 36% growth. Q: Which Snowflake AI products are leading adoption and how do they work? A: Two products lead adoption: the coding agent Cortex Code and CoWork, which lets users query company data in conversational, plain language, and customers using them tend to consume more of Snowflake’s platform. These features are a central part of Snowflake AI-driven revenue growth because management says they make it easier for knowledge workers and builders to work with data and thereby increase usage. Q: How have margins been affected by Snowflake’s AI adoption? A: Fast-growing AI workloads carry a lower contribution margin, prompting management to trim the fiscal 2027 non-GAAP product gross margin guide to 74% from 75%. Management nevertheless raised its non-GAAP operating margin guide to 14.5% from 13.5% by slowing headcount growth and using AI internally, which shapes the net picture of Snowflake AI-driven revenue growth. Q: What near-term report will give the clearest test of whether the growth lasts? A: The fiscal Q3 2027 product revenue report is the cleanest near-term test, as management guides 37% to 38% product revenue growth for that quarter. In May Snowflake guided Q2 to 30% and delivered 37%, so meeting or missing the new range will materially affect views of Snowflake AI-driven revenue growth. Q: What signs would indicate the recent lift is a pull-forward of projects rather than lasting demand? A: Falling short of the fiscal Q3 guidance, rising cloud costs that pressure gross margin without offsetting operating efficiencies, delayed large-customer migrations, or weaker sustained AI engagement would support a pull-forward explanation. Observing any of those developments would cast doubt on the sustainability of Snowflake AI-driven revenue growth. Q: How are large customer migrations contributing to higher usage on Snowflake? A: Existing workloads are arriving faster as large customers migrate to Snowflake, with one major Australian bank moving its financial crime platform and a network equipment manufacturer compressing a migration that likely would have taken two to three years into less than three quarters. Those accelerated migrations are helping drive Snowflake AI-driven revenue growth by shifting more workloads onto the core data platform. Q: How is Snowflake using AI internally, and how does that affect operating costs? A: Snowflake uses its own AI tools to reduce reliance on headcount, citing examples where CoWork brought marketing search optimization in-house and a planning process that needed three people now runs with one analyst. Those internal efficiencies helped management raise the fiscal 2027 non-GAAP operating margin guide and partially offset the higher cloud costs associated with Snowflake AI-driven revenue growth. Q: Which metrics should stakeholders monitor to judge the sustainability of Snowflake AI-driven revenue growth? A: Key metrics to watch are product revenue growth versus guidance, cohort ramp behavior (such as newer cohorts reaching 80% of purchased consumption faster), gross margin trends and cloud-cost dynamics, and disclosure on AI-driven consumption. The fiscal Q3 2027 result and whether cohorts sustain faster usage are particularly important indicators of durability.