Goldman Sachs Communacopia + Tech Conf 2025: Snowflake CEO Sridhar Ramaswamy on AI, Data Platforms, and Ent. Transformation

Key Takeaways

TL;DR: SNOW is laser-focused on evolving from a data warehouse to a full-stack ent. data + AI platform. New product launches (Snowflake Intelligence, OpenFlow, Postgres/Crunchy, and expanded data eng. via Iceberg/Spark) aim to expand TAM and sustain high consumption-based growth. Mgmt sees GenAI as a core secular tailwind (already in ~25% of deployed use cases) and is revamping GTM (sales, partnerships, prod. specialist overlays) to accelerate the path to $10B rev. The consumption model is a key differentiator and risk mitigant vs. failed AI projects elsewhere. Execution, depth of prod. integration, and onboarding new workloads outside the trad. Snowflake warehouse are top near-term priorities.

Key Topics & Investment Highlights

1. Product Strategy & Platform Expansion

• Shift to “All-Encompassing Data Platform”:
  • CEO: “We came off history as an analytic platform…now aiming to be an all-encompassing data platform from data inception to insights.”
  • AI as consumption layer & accelerant: AI is “a massive accelerant of the value creation cycle.”
• Boosting Data Eng. w/ Iceberg & Spark:
  • Iceberg unlocks ext. data lake workloads: “Iceberg…unlocks all data on cloud storage that can now be acted upon by Snowflake.”
  • Spark Connect enables native processing: “Super easy to run spark jobs…right inside Snowflake. Performance as the data processing engine is the best out there.”
  • Execution focus: “Very much getting started…OpenFlow and Spark Connect rollout will unlock data eng. in a big way.”
• Transactional & App Workloads (Unistore, Postgres/Crunchy):
  • OLTP expansion: “Acquired…Crunchy. It’s a Postgres DB…significantly expands our TAM while keeping the product cohesive.”
  • Goal: Enable SNOW customers to build transactional apps natively.

2. AI/GenAI as Core Growth Driver

• Snowflake Intelligence (Agentic Platform):
  • Flagged as top new product: “Snowflake Intelligence right up on top. It’s an agentic platform…internally at Snowflake a good number are using it…scaling it.”
  • Unique functionality: “Access to all…sales info…answers Qs I wouldn’t have dreamed of six months ago.”
  • Still early for rev.: “No great rev. numbers yet, but feels like a before/after moment.”
• AISQL—AI Embedded in SQL Primitives:
  • “Introduces AI primitives into SQL…lets people use AI on huge data w/o worrying about capacity/failures…handles all data processing.”
  • Use Cases: “Customers 100% use that for sentiment feedback…”
• GenAI Already Embedded in Customer Workloads:
  • Quantified progress: “~25% of deployed use cases have some AI element.”
  • Industry context: GenAI is a secular, non-zero-sum opp., “not a unipolar/bipolar world…OpenAI has run off w/ consumer attention.”

3. GTM, Consumption, & Rev. Growth Strategy

• Consumption-based model as risk mitigant:
  • “You don’t spend unless people use the product…If no consumption, no $ to pay.”
  • Positioned vs. failed ent. AI deployments: “Removes a lot of angst…95% of projects not doing well…”
• Sales & Channel Transformation:
  • New CRO (Mike Gannon): Driving “specialist team” overlays for new products, but avoiding excess overlays.
  • Field team enabled for broader AI use cases: “Field sales team can do many simple AI use cases.”
  • Partner ecosystem overhaul: “Rebooted partnership approach…new head of partners from AWS.”
  • Large hiring to support growth: “Hired 800 in H1 just into that function.”
• More Quantitative Approach to Consumption:
  • “Track use cases carefully…standardize…measure incremental consumption.”
  • “Difference between 90th percentile acct, our sales rep, and the median.”
  • Moving to $10B rev. milestone: “AI can be a big pull for how data is brought into Snowflake…That’s going to drive us…faster to $10B.”

4. Competitive Positioning & Mkt Opp.

• Core Value Prop:
  • Competing w/ “the giants…the Googles and Metas…world-class tech in data that lets them compete on even playing field.”