Whitepaper · from Snowflake
Building Trusted AI: Data Platform Essentials
As organizations rush to deploy AI at scale, the stakes for getting trust right have never been higher. Massive datasets — often including sensitive data — are now at the heart of business operations, and companies need
- Format
- Whitepaper
- Published by
- Snowflake
- Category
- AI Strategy & Governance
- Added
- 10 Sept 2026
About this whitepaper
As organizations rush to deploy AI at scale, the stakes for getting trust right have never been higher. Massive datasets — often including sensitive data — are now at the heart of business operations, and companies need to share and analyze their enterprise data while safeguarding it, following regulatory compliance and maintaining resilience.
To harness powerful AI agents and applications, companies need a unified data platform that’s both powerful and easy to use, deeply connected and fundamentally trusted. This requires a cohesive approach that integrates six critical elements from the ground up:
- Governance
- Security
- Privacy
- Interoperability
- Business continuity and disaster recovery
- Observability
This guide dives deep into these core tenets of a trusted data platform and how an integrated approach enables you to deploy production-ready AI with more confidence and fewer compromises.
Listen or skim
Summaries are generated from this page’s text. Read the full piece for the detail.
More from Snowflake
All 12 →
Delivering ROI for the Agentic Enterprise
The problem isn't ambition — it's execution. Organizations estimate a 41% failure rate for agentic initiatives launched over the next three years, according to the "ROI of Gen AI and Agents 2026" report. Agents can't
AI + Data Predictions 2026
In the enterprise, agentic AI will start as “micro-agents” that expand into more effective tools. Key industry developments will include:
The Essential Guide to Data Sharing
The ability to share data quickly and securely, both inside and outside an organization, is mission-critical to success in the age of AI. However, traditional methods for data sharing can be cumbersome, resulting in
Elsewhere in AI Strategy & Governance
See the category →
The State of AI Governance
The State of AI Governance: The Enterprise Governance Gap - Trillions of Tokens, Zero Governance explores how rapidly enterprise AI adoption is outpacing the controls needed to govern it. Based on anonymized production
AI Governance in Action
AI Governance in Action: A Strategic Guide is a practical ebook designed to help organizations understand, manage, and govern enterprise AI adoption. Using the fictional Kong Air case study, the guide explores
AI Governance Toolkit
Building AI governance one policy at a time invites gaps—and by the time you find them, the damage is done. A more effective path is to start deliberately, prove value quickly, and scale from there. Workiva's AI