80% of enterprise AI pilots never reach production. Not because the technology failed — because the foundation wasn’t right.
I watched a retail client spend 4 months building an Agentforce agent. Launched to 3,000 customers. Rolled back by Friday. A stale integration nobody had tested under real load.
We rebuilt on a clean foundation — one use case, governed, load-tested. Second launch held. 80% adoption in 30 days.
Three things that kill AI pilots:
❌ Dirty data → agent gives wrong answers → team stops trusting it in week two
❌ No success metric → CFO pulls budget → nobody can say what it delivered
❌ No governance → legal shuts it down → couldn’t prove compliance when asked
Before your next AI initiative — four questions:
- Is your CRM data clean enough for an agent to act on?
- Do you have one measurable outcome with a deadline?
- Have you load-tested at real data volumes in sandbox?
- Is your governance operational — not just documented?
If any answer is no — fix the foundation first. The agent will follow.
⏱ AI readiness audit: 8–12 hrs with a senior consultant.
💬 What broke first in your AI pilot?
