Your Complete Guide To Snowflake Summit 2026

Published on May 27, 2026

June 1–4, 2026 | Moscone Center, San Francisco

The data and AI conference calendar has no shortage of events in 2026, but Snowflake Summit 2026 is in a category of its own. With more than 20,000 attendees expected, 500+ sessions across 12 tracks, and a theme — "Making AI Real for Business" — that signals a genuine industry inflection point, this is the week where enterprise data teams stop debating agentic AI and start watching it ship.

Whether you're finalizing your travel plans or still deciding whether to go, this guide covers everything you need: dates, keynotes, session tracks, tips for making the most of four days on the floor, and (if you care about what happens after your agents are deployed) where to find us.

What is Snowflake Summit 2026, and why does it matter this year?

Snowflake Summit is Snowflake's annual flagship user conference. It’s at this event where the company makes its biggest product announcements, customers share real-world results, and the broader ecosystem of partners, analysts, and practitioners comes together to take stock of where the industry is heading.

The 2026 edition is the largest Summit to date. Over 20,000 attendees are expected in person, with additional virtual participation. The mix spans data engineers and architects, analytics leaders, CDOs, and data governance teams, application developers, and ISV partners spanning 190+ organizations. If you work in data, AI, or both, this is the room your peers will be in.

What makes Summit 26 specifically worth paying attention to: the theme isn't aspirational. "Making AI Real for Business" is a direct signal that Snowflake, and the ecosystem around it , is moving the conversation from AI experimentation into production-grade, governed, agentic AI at enterprise scale. The product announcements, the session tracks, and the keynote lineup all reflect that shift.

Dates, location, and logistics: Know before you go

Dates: June 1–4, 2026
Venue: Moscone Center, San Francisco, CA
Registration: Full conference passes are $2,295; group pricing (parties of five or more) starts at $1,695 per person. Online registration closes May 31, 2026.
Format: In-person attendance plus virtual access options

Moscone Center sits in San Francisco's SoMa neighborhood, within walking distance of a dense cluster of hotels, restaurants, and transit options. If you're booking accommodation, the blocks immediately surrounding Moscone fill up fast for events of this size; early booking is strongly advised.

Evenings at Summit include Snowbash, the conference's signature networking event, which in past years has been one of the more productive parts of the week for building partnerships outside the session schedule.

The theme driving everything: Making AI real for business

Every major conference has a theme. What makes this year’s theme worth taking seriously is that Snowflake is backing it with concrete product releases. The announcements expected this year include Snowflake Openflow, Adaptive Compute, Cortex AISQL, Snowflake Intelligence, and agentic products on the Snowflake Marketplace — a portfolio that, taken together, reflects a platform orientation toward intelligent, agent-driven experiences rather than standalone AI features.

For enterprise teams that have spent the past 18 months in AI pilots, this is the moment to pressure-test whether the tooling has caught up with the ambition. Summit 26 is where that conversation happens at scale, with practitioners who have shipped things, not just planned them.

Keynotes and speakers not to miss

Summit 26 structures its keynotes across the first three days, each pitched at a different audience:

Opening keynote — Monday, June 1 at 5:00 PM PDT Snowflake CEO Sridhar Ramaswamy in conversation with Anthropic Co-Founder and President Daniela Amodei. The pairing reflects how central the relationship between foundational AI models and enterprise data platforms has become — and this session is likely to set the tone for how Snowflake frames that intersection for the rest of the week. Based on the Summit theme, expect the conversation to focus on where production AI in the data cloud is heading, not just where it's been.

Platform keynote — Tuesday, June 2 Snowflake Co-Founder and President of Product Benoit Dageville and EVP of Product Christian Kleinerman take the stage for the session practitioners tend to circulate most: the product roadmap reveal. This is where new capabilities are announced and where partner and customer teams recalibrate their integration plans.

Builder keynote — Wednesday, June 3 at 9:00 AM PDT Live demos, technical depth, and practitioner stories focused on building, deploying, and scaling AI agents and applications on the Snowflake AI Data Cloud. If you're an architect or engineer, this is the one to be in the room for.

How to navigate 500+ sessions: the 12 tracks explained

With 500+ sessions across 12 official tracks, Summit 26 rewards a strategy. The full track list covers: What's New in Snowflake, Industry Innovation, Generative AI and Agents, Machine Learning, Architectures and Interoperability, and much, much more.

For data governance and AI-forward teams, two tracks are worth anchoring:

Governance and security: this track is where CDOs, data stewards, and compliance leads will find the most directly relevant content — policy automation, agentic oversight, and the frameworks emerging around compliant AI in production. As agents proliferate across enterprise stacks, governance stops being a checkbox and starts being an architectural requirement. This track reflects that shift.
Generative AI and agents: this track is where agentic architecture debates will play out live — which patterns are working in production, where knowledge and context management breaks down, and what "governed AI" actually looks like when you're running hundreds of agents across a complex data environment.

Also worth attention: Data Engineering and Pipelines for teams managing the foundations that feed agents, and Architectures and Interoperability for anyone thinking cross-platform. Note that 39 hands-on labs are available and tend to fill up: build your session schedule before you arrive.

How to make the most of your four days at Snowflake Summit 26

Four days at a 20,000-person conference can either be transformative or exhausting, depending almost entirely on preparation. A few principles that tend to separate productive Summit weeks from chaotic ones:

Lock your agenda before you land. Keynotes are standing-room-only; popular breakouts and all-hands-on labs have waitlists by day one. Build your schedule in advance and block the sessions that directly address your team's most pressing decisions.

Pre-book meetings with partners and vendors. To navigate the booth floor successfully, you'll need to meet with the right people. Most exhibitors offer pre-scheduled meeting slots, which get you past the demo loop and into a real conversation about your environment.

Come with sharp questions. The most useful conversations at Summit happen when you arrive with a specific problem — on governance, on production AI cost, on data quality in agentic workflows — and use the access to practitioners and vendors to pressure-test your thinking. Generic curiosity gets generic answers.

Don't skip Snowbash. Summit's evening event is perennially underrated as a networking venue. The informal setting is where partnerships and customer relationships actually start — often more efficiently than during formal session time.

Blend tracks deliberately. It's tempting to stay in one lane for four days. The more interesting conversations — and the more useful competitive intelligence — tend to come from crossing tracks. An engineering session can tell you more about governance gaps than a governance session sometimes will.

Meet Alation at Snowflake Summit 26: The knowledge layer your agents are missing

You already trust Snowflake with your data. But here's a question worth sitting with before Summit: what do your agents actually know?

Data context is not the same as organizational knowledge. An agent running on Snowflake has access to your data — but the institutional understanding of what that data means, which definitions are authoritative, which sources are trusted, and how governance policies should apply across systems? That lives somewhere else. Or, more often, it doesn't live anywhere consistently at all.

That's the problem Alation's Knowledge Layer is built to solve. It extends governance, data quality, and AI agents across your entire data stack — not just within Snowflake — and turns organizational knowledge into accuracy that compounds over time. Every product runs natively in Snowflake with pushdown compute and zero data movement, and works across every other platform in your stack.

Find us at booth #1303 for live demos of Data Quality for Snowflake, Agent Studio, and the Knowledge Layer architecture. Come with your hardest governance and AI accuracy questions.

Sessions to add to your Summit agenda

Building agents inside the knowledge layer: A financial services story Tuesday, June 3 | 4:00 PM | Session Code: G0104

Most organizations approach AI agents backwards — building the data foundation first, then figuring out which agents to deploy. The problem: you're never done with your foundations, and the business can't wait.

Satyen Sangani, CEO and co-founder of Alation, shares how a leading financial institution took a different path: starting with critical business outcomes, deploying agents inside the knowledge layer to reach them, and letting governance compound along the way — from regulatory compliance to automation to measurable business transformation.

Add to your calendar →

The new shadow IT: What happens when everyone ships agents Wednesday, June 4 | 10:30 AM | Session Code: AI124

A decade ago, SaaS allowed teams to bypass IT, reshaping governance and security across the enterprise. The same pattern is repeating with AI agents — only faster, and with higher stakes. When agents are spread across systems, knowledge becomes siloed. Without compounding feedback loops, agents don't improve. The result is a new form of shadow IT that most organizations aren't ready for.

Jonathan Bruce, VP & Field CTO at Alation, makes the case for a knowledge layer that spans platforms, preserves institutional IP, and improves agent accuracy through continuous evaluation — not a context layer locked inside the compute layer running the agents.