Quick Facts
- Gartner projects enterprise applications with task-specific agents will jump from less than 5% in 2025 to 40% by end of 2026
- Snowflake’s Cortex Code now has 50% customer adoption since launching in November 2025, with over 9,100 customers using Snowflake’s AI products weekly
- Both companies host major conferences in June 2026, with Snowflake Summit expecting over 20,000 attendees and Databricks focusing on data-intelligent apps and agents
Snowflake and Databricks are racing beyond their data platform origins to capture the next wave of enterprise AI adoption. Both companies are building what industry experts call “Systems of Intelligence” that organize enterprise data, trust, context and business logic for agent consumption.
The shift comes as personal agents emerge as the catalyst for broader organizational AI transformation. Snowflake announced major updates to Snowflake Intelligence and Cortex Code in April 2026, with Cortex Code seeing rapid adoption by more than 50 percent of customers since its November 2025 launch.
“This is one of the most transformative moments we’re seeing in technology,” said Denise Persson, Chief Marketing Officer at Snowflake. “What people are building with AI, both individually and across enterprises, is nothing short of extraordinary.”
Snowflake Intelligence now functions as a personal agent for employees, connecting to company data while maintaining internal security and governance rules. The platform can automate routine tasks through natural language descriptions and includes new Model Context Protocol connectors and reusable artifacts.
Cortex Code expanded support to external data sources including AWS Glue, Databricks and Postgres. The platform connects to other AI agents via MCP and Agent Communication Protocol, bringing one governed AI agent to entire data stacks.
Early results show significant productivity gains. Telenav processes 20 terabytes of data monthly and reported that converting raw data into usable insights now takes minutes rather than weeks. Wolfspeed uses AI agents to monitor equipment performance and identify process issues before they cause delays.
The timing aligns with massive enterprise investment in agentic systems. Deloitte projects 75% of companies will invest in agentic systems this year. However, fewer than 2% of enterprises have deployed agentic AI at full production scale due to infrastructure limitations around autonomous, multi-system execution.
“Enterprise AI is moving from generation to orchestration to execution,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. “Snowflake’s focus on governed data as the foundation for action aligns with that shift.”
Both companies will showcase their AI strategies at major June conferences. Snowflake Summit 26 runs June 1-4 in San Francisco, while Databricks Data + AI Summit follows two weeks later, focusing on data-intelligent applications and agent convergence.
The competitive landscape reflects a fundamental shift in enterprise architecture. Data platforms are evolving from passive storage to active intelligence systems where predictive models, copilots and autonomous agents consume data directly for automated decision-making.
Read more: Personal agents light the fuse as Snowflake and Databricks move up the AI stack