Many organizations delay commercial AI initiatives because their CRM data is incomplete, inconsistent, or poorly maintained. According to consultants at Blue Ridge Partners, waiting for perfect data often means waiting indefinitely.
The firm’s research suggests that commercial teams can often generate value from AI without first fixing every data quality issue. The key is to focus on narrowly defined use cases — such as cross-selling, upselling, and sales enablement — where imperfect data can still produce actionable insights.
Erica Summers, managing partner at Blue Ridge, said that imperfect data does not have to stall AI success in commercial applications. What matters is narrowing the scope, engineering actionable signals, and embedding AI into real workflows.
“Success correlates with aligning people, processes, and technology — not tool-chasing,” she told CRM Buyer.
Why Commercial AI Projects Stall
