Checklist
The AI Data Readiness Checklist
Built for teams evaluating or expanding Agentforce, Microsoft Copilot, or any AI agent built on top of Salesforce
Your AI agent is only as reliable as the data it runs on. Most enterprise Salesforce instances aren’t ready.
88% of enterprise AI agent pilots fail to reach production. The models are capable. The agent frameworks work. The bottleneck is almost always the same: the CRM data underneath is incomplete, fragmented, and only half-trustworthy.
This checklist gives revenue and RevOps teams a practical, honest assessment of where their Salesforce data stands before deploying Agentforce, Copilot, or any AI agent built on top of CRM. 33 checkpoints across 5 categories to give you a clear picture of what’s in place and what isn’t.
What you’ll walk away with:
- A category-by-category audit of your data foundation across completeness, identity resolution, unification, governance, and monitoring.
- Clarity on which gaps will cause your AI agents to fail first. And in which order to fix them.
- Specific checkpoints on the data problems most teams don't know to look for: partner-attributed activities, deduplicated activity records, meeting intelligence capture, bounced contact suppression, and junk filtering.
- A reference your team can return to as you scale AI use cases across the GTM lifecycle.
See how Nektar closes the gaps this checklist surfaces automatically.
Nektar captures every customer interaction and writes it into Salesforce without any rep input.
