Snowflake Q2 FY 2027: CoCo and CoWork Expand AI Consumption

Snowflake Q2 FY 2027 CoCo and CoWork Expand AI Consumption

Analyst(s): Futurum Research
Publication Date: September 8, 2026

Snowflake Q2 FY 2027 earnings show a business benefiting from AI-assisted development tools, customer expansion, and stronger consumption across core data workloads. The quarter also signals that Snowflake’s AI Data Cloud strategy is starting to shape customer behavior, especially around CoCo, CoWork, and Cortex AI.

What Is Covered in This Article:

  • Snowflake’s Q2 FY 2027 financial results
  • CoCo adoption driving platform usage
  • CoWork expanding agentic AI engagement
  • Product velocity supporting AI Data Cloud
  • Guidance and Final Thoughts

The News: Snowflake (NYSE: SNOW) announced financial results for Q2 FY 2027. Revenue was $1.55 billion, up 35% year over year (YoY), above Wall Street consensus of $1.49 billion. Product revenue was $1.49 billion, up 37% YoY. Professional services and other revenue was $54.9 million, up 0.8% YoY. Non-GAAP operating profit increased to $237 million from $127.6 million in the prior year and the corresponding margin was 15%, up more than 400 basis points YoY. Non-GAAP diluted earnings per share was $0.62, increasing from $0.35 in Q2 FY 2026.

“AI continues to compound our advantages, creating a flywheel effect across the business. CoWork and CoCo are driving transformational outcomes for our customers, while fueling rapid adoption, user growth, new workloads, and overall platform consumption,” said Sridhar Ramaswamy, chief executive officer of Snowflake. “Our rapid pace of innovation, tight go-to-market execution, and operational discipline position us well to capture the opportunity ahead. The Agentic Enterprise runs on Snowflake, and we’re just getting started.”

Snowflake Q2 FY 2027: CoCo and CoWork Expand AI Consumption

Analyst Take: Snowflake’s Q2 FY 2027 results show that AI is becoming a material consumption driver rather than a separate product narrative. The company’s AI-assisted tools are pulling customers into higher usage patterns across both new AI workloads and core data workloads. The quarter makes that case more credible, but it also raises expectations for repeatable consumption growth. Snowflake now has to convert broad AI interest into scaled enterprise deployments with measurable business outcomes.

CoCo Turns AI Coding Into a Consumption Driver

CoCo has become one of Snowflake’s clearest AI adoption signals, with more than 2,000 customer accounts starting to use it during the quarter. That brought total CoCo adoption to more than 9,100 accounts, giving Snowflake a large base for AI-assisted data engineering usage. CoCo’s value is tied to migration, code generation, and workflow acceleration, which can create incremental consumption inside existing accounts. Customer examples, including Sayari using CoCo to accelerate the migration of 12 billion records, show how AI tooling can attach to high-volume data movement. The more Snowflake embeds CoCo into migration and modernization projects, the more it can turn developer productivity into platform usage. CoCo is becoming a practical entry point for Snowflake to expand its share inside enterprise data engineering budgets.

CoWork Moves Snowflake Further Into Agentic Workflows

CoWork expanded to 5,800 accounts, extending Snowflake’s AI story beyond code assistance and into broader agentic work patterns. The strategic value comes from giving users a more direct interface to enterprise data, context, and task execution. Snowflake’s positioning improves when AI agents operate inside the governed data environment rather than outside it. That matters because enterprises want AI tools that can act on trusted data without creating new control gaps. CoWork also gives Snowflake another way to connect AI usage with core platform consumption, especially in accounts already using Snowflake for analytics and data sharing. The agentic workflow push increases Snowflake’s relevance beyond data warehousing and into operational AI use cases.

Product Velocity Broadens Snowflake’s AI Data Cloud Ambition

Snowflake launched more than 330 product capabilities to general availability in the first half of FY 2027, up 35% YoY. That pace matters because the company is trying to reposition its platform as a control layer for enterprise data, AI, applications, and agents. Cortex Sense and Cortex AI Gateway extend Snowflake’s AI portfolio into business context and action-oriented AI workflows. The Natoma integration adds to that direction by helping connect insights with execution. Customer wins such as 1Password and Indeed show that Snowflake is competing for broader data and AI transformation programs, not only analytics modernization. Product velocity gives Snowflake more routes into enterprise AI budgets, but it also increases the need for clear packaging and measurable outcomes.

Guidance and Final Thoughts

Snowflake guided Q3 FY 2027 product revenue to $1.588 billion to $1.593 billion, above Wall Street consensus of $1.51 billion, while adjusted operating margin is expected to reach 15.5%. For FY 2027, the company raised product revenue guidance to $6.07 billion from $5.84 billion, above consensus of $5.86 billion. Snowflake also increased its FY 2027 adjusted operating margin outlook to 14.5% from 13.5%, indicating that stronger consumption is translating into improved operating leverage alongside revenue growth.

The next test is whether Snowflake can turn rapid adoption of CoCo, CoWork, and Cortex AI into sustained consumption across larger enterprise deployments. AI-assisted migration, data engineering, and agentic workflows create additional routes for customers to consume the platform, while the breadth of new product capabilities expands Snowflake beyond its traditional analytics base. The simultaneous increase in product revenue and operating margin guidance is important because it suggests the company can fund faster product development without sacrificing leverage. If Snowflake can convert AI experimentation into recurring production workloads while maintaining this balance between growth and profitability, then AI could extend the current consumption acceleration rather than simply provide a temporary uplift.

See the full press release on Snowflake’s Q2 FY 2027 financial results on the company website.


Declaration of generative AI and AI-assisted technologies in the writing process: This content has been generated with the support of artificial intelligence technologies. Due to the fast pace of content creation and the continuous evolution of data and information, The Futurum Group and its analysts strive to ensure the accuracy and factual integrity of the information presented. However, the opinions and interpretations expressed in this content reflect those of the individual author/analyst. The Futurum Group makes no guarantees regarding the completeness, accuracy, or reliability of any information contained herein. Readers are encouraged to verify facts independently and consult relevant sources for further clarification.
Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.
Read the full Futurum Group Disclosure.

Other Insights From Futurum:

5 Reasons Snowflake Acquiring Observe Sets the Tone For 2026

At Snowflake Summit, the ‘Snowmentum’ Was Palpable

Snowflake Q1 FY 2027: AI Products Drive Faster Consumption Growth

Author Information

Futurum Research
Futurum Research

Futurum Research delivers forward-thinking insights on technology, business, and innovation. Content published under the Futurum Research byline incorporates both human and AI-generated information, always with editorial oversight and review from the expert Futurum Research team to ensure quality, accuracy, and relevance. All content, analysis, and opinion are based on sources and information deemed to be reliable at the time of publication.

The Futurum Group is not liable for any errors, omissions, biases, or inadequacies in the information contained herein or for any interpretations thereof. The reader is solely responsible for any decisions made or actions taken based on the information presented in this publication.

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