This is Growth! Growth Pill: AI Won’t Save You If Your Data Is Trash
Nov 26, 2025
Messy data is a significant hurdle for AI, especially in customer success. AI depends on reliable data for effective outcomes, but poor data leads to poor results. The discussion highlights that AI can actually clean up chaotic data through enrichment, unstructured data ingestion, and continuous updates. By prioritizing data accuracy first, organizations can better leverage AI, laying a solid foundation for enhanced customer experiences. It’s clear that fixing data issues is essential before diving into more advanced AI applications.
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Messy Data Blocks AI Value
- Messy data is the primary reason Customer Success teams fail to get value from AI.
- Daphne Costa Lopes says AI can't patch years of poor data governance the way humans have been able to.
AI Needs Trustworthy Context
- AI requires context and trustworthy data to act autonomously for customers.
- Without reliable reports, leaders can't trust AI agents to coordinate customer experiences, per Daphne Costa Lopes.
Clean Data With AI First
- Use AI first to enrich and clean your data before building customer-facing agents.
- Daphne Costa Lopes recommends enriching missing fields, ingesting unstructured sources, and keeping data current on intervals.