Key Takeaways from Snowflake SKO Partner Sessions: Partner Motions, Cortex, and What’s Next for Enterprise AI

The Snowflake Sales Kick Off (SKO) Partner Sessions made one thing clear: the focus has shifted from “what the tech can do” to “how we deliver it responsibly.” As a proud sponsor of this year’s SKO, our team had a front-row seat to these evolving strategies. The core themes of the event centered on a “Partner-First” execution model, the acceleration of AI via Snowflake Cortex, and the continued push toward governed, outcome-oriented implementations. Below is a look at the themes that stood out - and what they mean for enterprises building on Snowflake.

1) “Partner First” as an Operating Theme

A consistent message throughout the sessions was a stronger emphasis on “Partner First” execution. Snowflake aims to engage partners earlier in the customer journey to reduce friction between sales and delivery.
For customers, the practical implication is straightforward: initiatives that span data foundations, governance, and AI adoption are increasingly positioned as multi-party efforts. Partners are no longer just “implementers” but rather strategic guides who translate platform features into repeatable business value.

2) Co-Sell Motions and Partner Activation Are Becoming More Structured

Partner alignment is becoming more disciplined. Snowflake is moving away from informal collaborations toward structured activation, ensuring that sellers and partners align early on the specific customer problem and the pathway to success.

New Standards: This includes increased focus on partner certifications, documented use cases in the Snowflake Partner Network (SPN), and a push for partners to operationalise "co-sell readiness."

The Benefit: Customers can expect clearer delivery patterns and less ambiguity regarding roles and responsibilities throughout a program.

3) Cortex Accelerates Delivery; Differentiation Shifts to Governance

Snowflake Cortex is fundamentally changing the speed of development. By embedding AI and code assistance directly into the platform, Snowflake is drastically shortening implementation cycles. As delivery becomes more streamlined, differentiation shifts toward:

• Governing data and AI usage (security, privacy, compliance, access controls)

• Selecting the right use cases and sequencing them effectively

• Enabling adoption across business and technical stakeholders

• Defining and tracking measurable outcomes beyond technical go-lives

This reflects a broader enterprise reality: faster build cycles only matter when they translate into trusted, adopted, and measurable business impact.

4) Data Readiness and Governance Remain the Foundation for Enterprise AI

A recurring theme at SKO was a sobering reality: most organisations still have work to do on their data foundations. "AI Transformations" often fail not because of the model, but because of:

• Poor data quality and consistency

• Lack of semantic alignment and shared definitions

• Weak operational processes for change control

AI readiness remains the non-negotiable prerequisite for scaling beyond isolated pilots.

5) Enterprise Agents and Repeatability

Snowflake also highlighted the momentum behind Enterprise Agents. We are moving past simple chat interfaces toward AI that executes tasks, orchestrates workflows, and supports complex decision-making.
The success pattern for these agents is becoming clear: start with bounded workflows, maintain human-in-the-loop guardrails, and measure performance against operational KPIs rather than just technical benchmarks.

Closing Thoughts

The SKO Partner Sessions reflected a broader market direction: AI is quickly moving from experimentation to operationalisation. As platforms accelerate build cycles, the determining factors become governance, adoption, and measurable outcomes.

For organisations building on Snowflake, the opportunity is to pair Cortex-enabled acceleration with disciplined execution, ensuring speed does not come at the cost of control, trust, or business value.