A RevOps Co-lab on building a data layer you can actually trust in the AI era.
Do you trust AI to amplify your best data, or your worst? It’s a double-edged sword that can either consume bad data, or help improve it.
Ops teams are now the architects of AI readiness, but most are still stuck patching problems instead of doing what they do best – design, steward, and strategize.
This Co-lab gathers three Ops leaders who are actively rebuilding their data layer for AI. Each one walks the audience through a working artifact from their own org — a framework, a flow, a governance model — not a vendor pitch, not a “future state” slide.
You will see exactly how they think, design, and operationalize trust in their data layer. The end-to-end approach for architecting things like:
- Source of truth: Which system wins for which object, and how do you resolve conflicts when Salesforce, Marketo, and product data disagree?
- Quality: Pre-flight checks, deduplication, normalization, and the “is this account real” problem.
- Governance: Ownership of fields, change management, lifecycle of an account record, who can break what.
- AI: What’s trusted, what’s not, and lessons learned for the AI era
Stop fixing gaps. Start designing the bridge across them.
