CEO: Behind the Scenes Stop chasing AI cost savings and start fixing your data foundation
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Dec 15, 2025 Marc Potter, CEO of Actian and expert in data intelligence, discusses the pitfalls of chasing AI cost savings without a solid data foundation. He highlights the urgency for organizations to address data quality to prevent poor AI outcomes. Marc introduces the concept of governance-by-design, stressing the importance of classifying data correctly. He also offers insights on how to drive AI adoption through education and clear use cases, plus the need for thoughtful, value-driven AI strategies instead of rushed implementations.
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AI Needs Trustworthy Data First
- AI requires high-quality, trustworthy data because training on poor data produces hallucinations.
- Actian's mission is to provide AI-ready data so decisions can be trusted.
Shift Left With Governance By Design
- Shift left and validate data the moment it arrives to maintain quality throughout its lifecycle.
- Provide visibility into origins and usage so executives can trust and govern their data.
Context Is The Missing Ingredient
- Automated metadata discovery and a federated knowledge graph add essential context to data.
- Context prevents AI from making mere best guesses and reduces errors.