On April 21, 2026, Snowflake announced significant expansions to Snowflake Intelligence and Cortex Code — its bid to become what the company calls the “control plane for the agentic enterprise.” In plain terms: Snowflake wants your company’s AI agents to live, reason, and act from inside its data platform. More than 9,100 Snowflake customers are now using its AI products weekly, and over half of all customers have already adopted Cortex Code since its late-2025 launch.

Key takeaways:

• Snowflake announced April 21 updates making its platform a unified control layer for enterprise AI agents.
• Snowflake Intelligence now connects to Gmail, Google Calendar, Jira, Salesforce, and Slack via MCP connectors.
• Over half of Snowflake customers already use Cortex Code to accelerate development workflows.
• More than 9,100 Snowflake customers use its AI products weekly, per the company’s press release.
• A Snowflake Intelligence iOS mobile app enters public preview soon, enabling data queries on the go.

This isn’t a minor product refresh. It’s Snowflake’s clearest statement yet that the data warehouse is evolving into the operating layer for enterprise AI — a position it’s fighting hard to own before the AI agent market consolidates around a handful of incumbents.

What Is the “Agentic Enterprise,” and Why Does It Matter?

The phrase “agentic enterprise” describes a company where AI systems don’t just answer questions — they take action. Instead of asking your BI tool “what were last quarter’s sales?” an agentic system automatically surfaces the answer, identifies the anomaly, drafts the follow-up email, and schedules the review meeting. The human stays in the loop for judgment calls; the agent handles orchestration.

Snowflake’s announcement is a direct response to this shift. Snowflake Intelligence — the company’s AI agent layer for business users — now acts as a “personal work agent” that learns individual preferences over time. The system can automate routine tasks described in plain language (preparing presentations, multi-step analysis, sending follow-ups), connect to enterprise tools through new MCP connectors, and generate multi-step cited research reports using a new “deep research” feature.

The Model Context Protocol (MCP) connectors being rolled out include Gmail, Google Calendar, Google Docs, Jira, Salesforce, and Slack. This is significant: it positions Snowflake as the data-governed hub through which AI agents reach into every tool employees already use — rather than each tool having its own isolated AI assistant.

Adobe made a similar move at Summit 2026, launching CX Enterprise to scale agentic workflows. The pattern across major enterprise platforms is the same: the goal is to own the control layer before agents proliferate and require centralized governance.

What Does Cortex Code Change for Technical Teams?

Cortex Code is Snowflake’s AI coding agent, and since its late-2025 launch it has quietly become one of its fastest-adopted products — more than half of Snowflake’s customer base is already using it per the company’s April 21 announcement.

The April updates expand Cortex Code significantly beyond Snowflake-native data. Developers can now build applications against external data sources — Amazon Web Services Glue, Databricks, and PostgreSQL — without migrating data into Snowflake first. The platform also integrates with Visual Studio Code and includes a plugin for Anthropic’s Claude Code — announced alongside these updates in April 2026 — meaning teams already running Claude Code as their coding agent can now connect it to Cortex Code’s data-native capabilities directly.

Other new Cortex Code capabilities include:

• Browser-based sandboxes for running code without local environment setup
• Python and TypeScript SDKs for embedding Cortex Code into existing applications
• Workflow previewing before execution to verify behavior before agents act
• ACP (Agent Communication Protocol) integration for interoperability with external agent frameworks

For technical leaders, this matters because it lowers the cost of building enterprise AI tools against governed data. The pattern emerging across AWS Bedrock’s stateful runtime and now Snowflake Cortex Code is the same: production-grade AI agents need persistent memory, data access, and orchestration — and major platforms are all racing to supply that stack.

Is Snowflake Actually Differentiated Here?

The “control plane” framing is ambitious, and Snowflake isn’t alone in making it. Microsoft positions Copilot as the agentic layer across Microsoft 365. Google is building agents for employees, workflows, and customers across Workspace. Salesforce’s Agentforce sits in the CRM layer.

What Snowflake is betting on is data governance as differentiation. The argument from Baris Gultekin, VP of AI at Snowflake: “Snowflake gives customers one place to bring their data together, connect the systems they rely on, and turn AI into something that actually helps teams get work done.”

The key phrase is “one place.” Snowflake’s stated rationale — echoed by Gartner’s 2025 research on AI implementation failures — is that most enterprise AI pilots stall not because the model is weak, but because agents can’t reliably access accurate, governed, up-to-date data. Snowflake’s pitch is that it already holds that data for thousands of enterprises — and it’s now making it actionable through agents rather than just queryable through SQL.

Named enterprise customers already deploying on the platform include Capita, Logitech, Telenav, United Rentals, and Wolfspeed, per the announcement.

What Should Business Leaders Watch?

The immediate question for any organization running Snowflake is whether to accelerate AI build-out on the platform rather than assembling point solutions. The MCP connector set — Gmail, Jira, Salesforce, Slack — covers the most common enterprise workflow surfaces. If your team’s data is already in Snowflake, the friction to deploy agents that act on it is dropping substantially.

The longer-term question is vendor concentration. Centralizing data, models, and agent orchestration in a single platform creates deep lock-in. That may be a reasonable trade for governance and reliability — or it may be a strategic risk as the AI tooling landscape continues to evolve rapidly.

Neither answer is obvious yet. What is clear is that Snowflake is moving faster toward production agent infrastructure than the “data warehouse” label suggests, and business leaders who still think of it as a query engine are behind the actual product roadmap.

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Frequently asked questions

What is Snowflake Intelligence?

Snowflake Intelligence is an AI agent layer for business users within the Snowflake platform. As of April 2026, it can automate routine tasks, connect to enterprise tools like Gmail, Jira, Salesforce, and Slack via MCP connectors, generate multi-step cited research reports, and personalize responses over time by learning user behavior — all grounded in the organization’s governed Snowflake data.

What is the “agentic enterprise” Snowflake is targeting?

The agentic enterprise refers to organizations where AI systems take autonomous action across workflows — not just answering questions but completing tasks, triggering follow-ups, and orchestrating multi-step processes. Snowflake’s April 21, 2026 announcement positions its platform as the central “control plane” through which those agents access data and connect to business tools.

How many companies use Snowflake’s AI products?

Per Snowflake’s April 21, 2026 press release, more than 9,100 customers use its AI products on a weekly basis. More than half of Snowflake’s total customer base has adopted Cortex Code since its launch in late 2025.

What is Cortex Code and how does it differ from GitHub Copilot?

Cortex Code is Snowflake’s AI coding agent, focused specifically on data-centric development. Unlike general-purpose coding assistants, it works natively with Snowflake’s data governance layer and can now extend to external data systems like AWS Glue, Databricks, and PostgreSQL. It also integrates with VS Code and includes a plugin for Anthropic’s Claude Code. Think of it as a coding agent purpose-built for data engineering and analytics work.

Does this announcement affect organizations not using Snowflake?

Indirectly, yes. The broader trend Snowflake is responding to — AI agents that need unified, governed data access to take reliable action — is not Snowflake-specific. Every enterprise AI stack will face the same challenge. Competing control-plane bids from Microsoft, Salesforce, Google, and AWS mean the market for “who governs your enterprise AI agents” is actively contested and will shape AI infrastructure decisions across most mid-to-large organizations over the next 18 months.

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Published April 22, 2026. Based on Snowflake’s official press release and SiliconAngle’s April 21 analysis.

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